Google_scholar_500_publications_run1.json

[{"title": "[PDF][PDF] Deep learning for large scale biodiversity monitoring", "title_link": "https://ccal.ucsc.edu/wp-content/uploads/2017/03/Klein_2015.pdf", "publication_info": "DJ Klein, MW McKown, BR Tershy\u00a0- Bloomberg Data for Good\u00a0\u2026, 2015 - ccal.ucsc.edu", "snippet": "\u2026 invested in is known as Deep Learning (DL) [31]. DL is a quickly growing and vibrant field; \nhere we summarize our use of DL and postulate how biodiversity monitoring can be improved \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3529778276177370458&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Wl1x_6NK_DAJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3529778276177370458&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Efficient Deep Learning Models for Categorizing Chenopodiaceae in the Wild", "title_link": "https://www.worldscientific.com/doi/abs/10.1142/S0218001421520157", "publication_info": "A Heidary-Sharifabad, MS Zarchi, S Emadi\u2026\u00a0- International Journal of\u00a0\u2026, 2021 - World Scientific", "snippet": "\u2026 Currently, the preferred approach for performing this work is deep learning. In this study, \nwe investigated whether deep learning can be used for helping to protect the biodiversity of \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4716785148250653242&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:OoJRCxpjdUEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4716785148250653242&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning improves acoustic biodiversity monitoring and new candidate forest frog species identification (genus Platymantis) in the Philippines", "title_link": "https://link.springer.com/article/10.1007/s10531-020-02107-1", "publication_info": "A Khalighifar, RM Brown, J Goyes Vallejos\u2026\u00a0- Biodiversity and\u00a0\u2026, 2021 - Springer", "snippet": "\u2026 In this study, we demonstrate the efficacy of deep learning technology for reliably identifying\u2014\u2026 \n, based on fully documented voucher specimens deposited in biodiversity repositories). \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13477966340297091322&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:-mgUKPpaC7sJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13477966340297091322&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning in deep time", "title_link": "https://www.pnas.org/doi/abs/10.1073/pnas.2020870117", "publication_info": "AE White\u00a0- Proceedings of the National Academy of\u00a0\u2026, 2020 - National Acad Sciences", "snippet": "\u2026 the biological basis of deep-learning\u2013based classifications. Advances in the science of \ndeep learning are coming rapidly and require time to be integrated in a biodiversity context. For \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9598979182007213076&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:FNzoXbVsNoUJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9598979182007213076&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Mapping Potential Plant Species Richness over Large Areas with Deep Learning, MODIS, and Species Distribution Models", "title_link": "https://www.mdpi.com/2072-4292/13/13/2490", "publication_info": "H Choe, J Chi, JH Thorne\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 imagery with species biodiversity data enables us to quantify biodiversity in inaccessible but \n\u2026 existing biodiversity data with remote sensing imagery to construct biodiversity information \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17760717170144222353&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:kZygeiq-evYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17760717170144222353&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning and computer vision will transform entomology", "title_link": "https://www.pnas.org/doi/abs/10.1073/pnas.2002545117", "publication_info": "TT H\u00f8ye, J \u00c4rje, K Bjerge\u2026\u00a0- Proceedings of the\u00a0\u2026, 2021 - National Acad Sciences", "snippet": "\u2026 However, there are very few examples of invertebrate biodiversity-related field studies \napplying deep learning models (23). Early attempts used feature vectors extracted from single \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6583818154135554404&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ZIkEh7prXlsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6583818154135554404&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automatic annotation of coral reefs using deep learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/7761105/", "publication_info": "A Mahmood, M Bennamoun, S An\u2026\u00a0- Oceans 2016 mts\u00a0\u2026, 2016 - ieeexplore.ieee.org", "snippet": "\u2026 bottleneck by developing advanced deep learning and computer vision \u2026 decline in our planet\u2019s \nmarine biodiversity [5]. Today\u2019s \u2026 a computer vision and deep learning based framework for \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6239260941069453091&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Iwdq1cROllYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6239260941069453091&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Detection and annotation of plant organs from digitised herbarium scans using deep learning", "title_link": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746675/", "publication_info": "S Younis, M Schmidt, C Weiland, S Dressler\u2026\u00a0- Biodiversity data\u00a0\u2026, 2020 - ncbi.nlm.nih.gov", "snippet": "\u2026 In this paper, we use deep learning for detecting plant organs on herbarium scans. The \nplant organs are detected using an object detection network, which works by localising each \u2026", "cited_by": "https://scholar.google.com/scholar?cites=18231003236088442853&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:5W8M6tmIAf0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=18231003236088442853&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Sashimi: A toolkit for facilitating high\u2010throughput organismal image segmentation using deep learning", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13712", "publication_info": "ST Schwartz, ME Alfaro\u00a0- Methods in Ecology and Evolution, 2021 - Wiley Online Library", "snippet": "\u2026 biodiversity from image databases. Image segmentation meta-algorithms using deep \nlearning \u2026 (CNNs) have been trained on a small fraction of biodiversity, thus limiting their utility. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13928925734357247907&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:oycpIyh8TcEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13928925734357247907&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for detection of bird vocalisations", "title_link": "https://arxiv.org/abs/1609.08408", "publication_info": "I Potamitis\u00a0- arXiv preprint arXiv:1609.08408, 2016 - arxiv.org", "snippet": "\u2026 analysis of their data can assist decision making in a wide spectrum of environmental services, \nsuch as: Monitoring of range shifts of animal species due to climate change., biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13184890222528758019&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:AwFZBM0j-rYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13184890222528758019&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Automated herbarium specimen identification using deep learning", "title_link": "https://hal.archives-ouvertes.fr/hal-01629142/document", "publication_info": "J Carranza-Rojas, A Joly, P Bonnet\u2026\u00a0- TDWG: Biodiversity\u00a0\u2026, 2017 - hal.archives-ouvertes.fr", "snippet": "\u2026 be used in transfer learning (a technique in deep learning that first allows training a model \nwith a \u2026 Our evaluation shows that the accuracy for species identification with deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15227707394770251379&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:c67eGDKvU9MJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15227707394770251379&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Automatic standardized processing and identification of tropical bat calls using deep learning approaches", "title_link": "https://www.sciencedirect.com/science/article/pii/S0006320719308961", "publication_info": "X Chen, J Zhao, Y Chen, W Zhou, AC Hughes\u00a0- Biological Conservation, 2020 - Elsevier", "snippet": "\u2026 monitor biodiversity across the landscape remain a gold-standard for biodiversity research, \nyet \u2026 provide a consistent tool for monitoring biodiversity for management and conservation. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13777504931448472119&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:N8ItIr2HM78J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13777504931448472119&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Image-based taxonomic classification of bulk biodiversity samples using deep learning and domain adaptation", "title_link": "https://www.biorxiv.org/content/10.1101/2021.12.22.473797.abstract", "publication_info": "T Fujisawa, V Noguerales, E Meramveliotakis\u2026\u00a0- bioRxiv, 2021 - biorxiv.org", "snippet": "\u2026 , the success of deep learning in taxonomy to date has been \u2026 deep learning for insect \nclassification based on bulksample images in real-world scenarios of high-throughput biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:wQaqETbyEhUJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=1518542338415789761&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1518542338415789761&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Scene\u2010specific convolutional neural networks for video\u2010based biodiversity detection", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13011", "publication_info": "BG Weinstein\u00a0- Methods in Ecology and Evolution, 2018 - Wiley Online Library", "snippet": "\u2026 My goal is to explore a pipeline for video-based biodiversity observation, describe its \u2026 I \nbuild on background subtraction tools introduced in Weinstein (2015) to add deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=18074128015007686824&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:qCB4N6sz1PoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=18074128015007686824&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] ACHENY: A standard Chenopodiaceae image dataset for deep learning models", "title_link": "https://www.sciencedirect.com/science/article/pii/S2352340921007599", "publication_info": "A Heidary-Sharifabad, MS Zarchi, S Emadi, G Zarei\u00a0- Data in brief, 2021 - Elsevier", "snippet": "\u2026 Biodiversity conservation of these species is critical due to the destructive effects of human \n\u2026 be facilitated by deep learning. The feasibility of applying deep learning algorithms to identify \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3483752475029377496&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=1ZSRk3MAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=3483752475029377496&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Modelling Animal Biodiversity Using Acoustic Monitoring and Deep Learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/9534195/", "publication_info": "C Chalmers, P Fergus, S Wich\u2026\u00a0- 2021 International Joint\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 in this paper, several deep learning approaches have been \u2026 hand-crafted features with deep \nlearning in an attempt to \u2026 , and those generated using deep-learning). They reported that an \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:KrcfI7ieFcEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=13913201137531467562&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13913201137531467562&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Technology developments for biodiversity monitoring and conservation", "title_link": "https://search.proquest.com/openview/fcace76f16e08bdfc2f0f79c4624e1ec/1?pq-origsite=gscholar&cbl=2049297", "publication_info": "S Kelling\u00a0- Biodiversity Information Science and Standards, 2018 - search.proquest.com", "snippet": "\u2026 to AI and Deep Learning. Computing: Investment and rapid growth in AI and Deep Learning \n\u2026 By taking a Deep Learning approach where the base layers of the model are built upon \u2026", "cited_by": "https://scholar.google.com/scholar?cites=248814521720871682&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ApshPn33cwMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=248814521720871682&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Whale counting in satellite and aerial images with deep learning", "title_link": "https://www.nature.com/articles/s41598-019-50795-9", "publication_info": "E Guirado, S Tabik, ML Rivas, D Alcaraz-Segura\u2026\u00a0- Scientific reports, 2019 - nature.com", "snippet": "\u2026 , which subsequently caused alterations in marine biodiversity and functions 7 . To prevent \n\u2026 Indeed, biodiversity conservation would certainly benefit from robust and automatic systems \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13240239720709040409&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=2nE7TNgAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=13240239720709040409&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Towards an IoT-based deep learning architecture for camera trap image classification", "title_link": "https://ieeexplore.ieee.org/abstract/document/9345858/", "publication_info": "IA Zualkernan, S Dhou, J Judas\u2026\u00a0- 2020 IEEE Global\u00a0\u2026, 2020 - ieeexplore.ieee.org", "snippet": "\u2026 Ecologists use wildlife population monitoring as an analytical tool to study and understand \nhow to maintain biodiversity. Camera traps are specialized cameras used by ecologists to \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15135029829242235010&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:gqjs3HBtCtIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[HTML][HTML] A deep learning method for accurate and fast identification of coral reef fishes in underwater images", "title_link": "https://www.sciencedirect.com/science/article/pii/S1574954118300694", "publication_info": "S Villon, D Mouillot, M Chaumont, ES Darling\u2026\u00a0- Ecological\u00a0\u2026, 2018 - Elsevier", "snippet": "\u2026 cost-effectively monitor marine biodiversity, yet it remains difficult \u2026 Deep Learning methods \ncan thus perform efficient fish \u2026 protocols for monitoring fish biodiversity cheaply and effectively. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=869129487282828080&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=juP1o-UAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=869129487282828080&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Applications for deep learning in ecology", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13256", "publication_info": "S Christin, \u00c9 Hervet, N Lecomte\u00a0- Methods in Ecology and\u00a0\u2026, 2019 - Wiley Online Library", "snippet": "\u2026 that deep learning has been used successfully to identify species, classify animal behaviour \nand estimate biodiversity in \u2026 We demonstrate that deep learning can be beneficial to most \u2026", "cited_by": "https://scholar.google.com/scholar?cites=12471331922673064448&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ANrqxk4SE60J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12471331922673064448&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning pipeline for automated visual moth monitoring: insect localization and species classification", "title_link": "https://dl.gi.de/handle/20.500.12116/37700", "publication_info": "D Korsch, P Bodesheim, J Denzler\u00a0- INFORMATIK 2021, 2021 - dl.gi.de", "snippet": "\u2026 of deep learning methods for visual monitoring is not yet established in biodiversity research\u2026 \nIn this paper, we present a deep learning pipeline for analyzing images captured by a moth \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13418548249249874769&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:UYP6xYlCOLoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[HTML][HTML] Deep learning for environmental conservation", "title_link": "https://www.sciencedirect.com/science/article/pii/S0960982219310322", "publication_info": "A Lamba, P Cassey, RR Segaran, LP Koh\u00a0- Current Biology, 2019 - Elsevier", "snippet": "\u2026 that use deep learning, in which performance issues can impact both biodiversity and human \nlives\u2026 Biased training data can potentially lead to erroneous outputs in these deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2704782120693537415&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=KR3AV20AAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=2704782120693537415&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "CityNet\u2014Deep learning tools for urban ecoacoustic assessment", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13114", "publication_info": "AJ Fairbrass, M Firman, C Williams\u2026\u00a0- Methods in ecology\u00a0\u2026, 2019 - Wiley Online Library", "snippet": "\u2026 As the main focus of the study was the development of algorithms for ecoacoustic \nassessment of biodiversity in cities, we conducted further analysis on the two best performing \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13300986854470552636&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:PIzbjhKZlrgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13300986854470552636&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Individual tree-crown detection in RGB imagery using semi-supervised deep learning neural networks", "title_link": "https://www.mdpi.com/2072-4292/11/11/1309", "publication_info": "BG Weinstein, S Marconi, S Bohlman, A Zare, E White\u00a0- Remote Sensing, 2019 - mdpi.com", "snippet": "\u2026 This approach opens the door for the use of deep learning in airborne biodiversity \nsurveys, despite the persistent lack of annotated data in the forestry and ecology datasets. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16021044574892348205&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=OviqAJsAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=16021044574892348205&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Augmentation Methods for Biodiversity Training Data", "title_link": "https://biss.pensoft.net/article/37307/download/pdf/", "publication_info": "M Lasseck\u00a0- Biodiversity Information Science and Standards, 2019 - biss.pensoft.net", "snippet": "\u2026 in deep learning. Reliable automatic species recognition provides a promising tool for \nbiodiversity \u2026 , neural network architectures, deep learning frameworks and computer hardware, a \u2026", "cited_by": "https://scholar.google.com/scholar?cites=817252168621560704&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:gBObcoR2VwsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=817252168621560704&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "BatNet++: A Robust Deep Learning-Based Predicting Models for Calls Recognition", "title_link": "https://ieeexplore.ieee.org/abstract/document/9260290/", "publication_info": "J Hu, W Huang, Y Su, Y Liu\u2026\u00a0- 2020 5th International\u00a0\u2026, 2020 - ieeexplore.ieee.org", "snippet": "\u2026 and it is a Ney research object of biodiversity-protection. In this paper, we introduce a \nnovel deep learning model to monitoribats and recognize bats species. There are quite a \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1926690173487185842&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:sn_wNoH6vBoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1926690173487185842&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] An automated deep learning based satellite imagery analysis for ecology management", "title_link": "https://www.sciencedirect.com/science/article/pii/S1574954121002430", "publication_info": "HM Alshahrani, FN Al-Wesabi, M Al Duhayyim\u2026\u00a0- Ecological\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 of deep learning models made the image classification highly effective. In this view, this \npaper presents a new parameter tuned deep learning \u2026 the measure and express biodiversity. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6125899220584487657&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:6drHfOKQA1UJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6125899220584487657&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Supporting citizen scientists with automatic species identification using deep learning image recognition models", "title_link": "https://search.proquest.com/openview/d73a8e41f0ccef7f9d0376817d6dffcf/1?pq-origsite=gscholar&cbl=2049297", "publication_info": "M Schermer, L Hogeweg\u00a0- Biodiversity Information Science\u00a0\u2026, 2018 - search.proquest.com", "snippet": "\u2026 deep learning technology, and discuss the possibilities and challenges. Keywords automated \nimage recognition, deep learning\u2026 - Citizen Science and Biodiversity Informatics for Natural \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7296868856489718415&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:jzKug5CvQ2UJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7296868856489718415&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Machine learning model for identifying Dutch/Belgian biodiversity", "title_link": "https://biss.pensoft.net/article/39229/download/pdf/", "publication_info": "L Hogeweg, M Schermer, S Pieterse\u2026\u00a0- Biodiversity\u00a0\u2026, 2019 - biss.pensoft.net", "snippet": "\u2026 We have developed a deep learning-based species \u2026 large number of species in a deep \nlearning model. We will evaluate the \u2026 provide large scale automated analysis of biodiversity data. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6432546901266755234&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:om4LW1P_RFkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6432546901266755234&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep learning approaches for natural product discovery from plant endophytic microbiomes", "title_link": "https://environmentalmicrobiome.biomedcentral.com/articles/10.1186/s40793-021-00375-0", "publication_info": "SA Aghdam, AMV Brown\u00a0- Environmental\u00a0\u2026, 2021 - environmentalmicrobiome\u00a0\u2026", "snippet": "\u2026 This review explores breakthrough approaches for natural product discovery from plant \nmicrobiomes, emphasizing the promise of deep learning as a tool for endophyte bioprospecting, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=12508016245997414158&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Dqd9Y4Fmla0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12508016245997414158&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning as a tool for ecology and evolution", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13901", "publication_info": "ML Borowiec, RB Dikow, PB Frandsen\u2026\u00a0- Methods in Ecology\u00a0\u2026, 2021 - Wiley Online Library", "snippet": "\u2026 We expect that rapid adoption of deep learning in ecology and evolution will continue, \nespecially in automation of biodiversity monitoring and discovery and inference from genetic data. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17381178253487095195&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:m73XOIhZNvEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17381178253487095195&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] A new method to control error rates in automated species identification with deep learning algorithms", "title_link": "https://www.nature.com/articles/s41598-020-67573-7", "publication_info": "S Villon, D Mouillot, M Chaumont, G Subsol\u2026\u00a0- Scientific reports, 2020 - nature.com", "snippet": "\u2026 In order to improve our model, we used data augmentation 41 on native biodiversity and \necosystem. Each \u201cnatural\u201d image yielded 4 more images: 2 with increased contrast (120% and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3288337413956252785&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=ADsWLkw1zrwC&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=3288337413956252785&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A deep learning approach to species distribution modelling", "title_link": "https://link.springer.com/chapter/10.1007/978-3-319-76445-0_10", "publication_info": "C Botella, A Joly, P Bonnet, P Monestiez\u2026\u00a0- \u2026\u00a0& Biodiversity Informatics, 2018 - Springer", "snippet": "\u2026 In this paper, we propose a deep learning approach to the problem in order to improve the \npredictive effectiveness. Non-linear prediction models have been of interest for SDM for more \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5902438991441767308&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=LzGLbYAAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=5902438991441767308&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Where is my deer?-wildlife tracking and counting via edge computing and deep learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/9278802/", "publication_info": "B Arshad, J Barthelemy, E Pilton\u2026\u00a0- 2020 IEEE SENSORS, 2020 - ieeexplore.ieee.org", "snippet": "\u2026 Abstract\u2014Reliable, informative and up-to-date information regarding the location, mobility \nand behavioral patterns of animals enhances our ability to preserve biodiversity, manage \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14025777703017676640&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:YH_2VoKSpcIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14025777703017676640&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Ecoacoustics: acoustic sensing for biodiversity monitoring at scale", "title_link": "https://www.researchgate.net/profile/Jerome-Sueur/publication/343395223_Ecoacoustics_acoustic_sensing_for_biodiversity_monitoring_at_scale/links/5f4ba204299bf13c5058e9db/Ecoacoustics-acoustic-sensing-for-biodiversity-monitoring-at-scale.pdf", "publication_info": "D Stowell, J Sueur\u00a0- Remote Sensing in Ecology and\u00a0\u2026, 2020 - researchgate.net", "snippet": "\u2026 and are complementary to other biodiversity monitoring techniques such as camera trapping\u2026 \nCityNet deep learning tools for urban ecoacoustic assessment. Methods Ecol. Evol, 10, 186\u2013\u2026", "cited_by": "https://scholar.google.com/scholar?cites=2240883883666928415&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:H3Pd_AQ4GR8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2240883883666928415&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Fusing shallow and deep learning for bioacoustic bird species classification", "title_link": "https://ieeexplore.ieee.org/abstract/document/7952134/", "publication_info": "J Salamon, JP Bello, A Farnsworth\u2026\u00a0- 2017 IEEE international\u00a0\u2026, 2017 - ieeexplore.ieee.org", "snippet": "\u2026 Automated c1assification of organisms to species based on their vocalizations would \ncontribute tremendously to abilities to monitor biodiversity, with a wide range of applications in the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8830159971339147589&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:RRmLsbUHi3oJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8830159971339147589&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Bat detective\u2014Deep learning tools for bat acoustic signal detection", "title_link": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005995", "publication_info": "O Mac Aodha, R Gibb, KE Barlow\u2026\u00a0- PLoS computational\u00a0\u2026, 2018 - journals.plos.org", "snippet": "\u2026 biodiversity monitoring and to manage the impact of anthropogenic change [1, 2]. Modern \nhardware for passive biodiversity \u2026 a powerful tool for understanding trends in biodiversity [3\u20136]. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1343254978967196988&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:PFUdWEkzpBIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1343254978967196988&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Identification of animals and recognition of their actions in wildlife videos using deep learning techniques", "title_link": "https://www.sciencedirect.com/science/article/pii/S1574954121000066", "publication_info": "F Schindler, V Steinhage\u00a0- Ecological Informatics, 2021 - Elsevier", "snippet": "\u2026 Biodiversity protection objectives were initially set for 2010 by the European Parliament, for \nexample, and then extended to 2020. The biodiversity \u2026 This study presents a deep learning-\u2026", "cited_by": "https://scholar.google.com/scholar?cites=9028655316484129788&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:_IN6qiw6TH0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9028655316484129788&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Discovering Patterns of Biodiversity in Insects Using Deep Machine Learning.", "title_link": "https://go.gale.com/ps/i.do?id=GALE%7CA646493764&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=25350897&p=AONE&sw=w", "publication_info": "C Earl, AE White, MG Trizna, PB Frandsen\u2026\u00a0- Biodiversity\u00a0\u2026, 2019 - go.gale.com", "snippet": "\u2026 in a broad range of biodiversity and evolutionary questions, \u2026 and collaboration to enrich \nbiodiversity knowledge, and \u2026 We present deep learning models (specifically, convolutional \u2026", "cited_by": "https://scholar.google.com/scholar?cites=33052269224134473&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=_a78jyIAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=33052269224134473&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Identifying land patterns from satellite imagery in amazon rainforest using deep learning", "title_link": "https://arxiv.org/abs/1809.00340", "publication_info": "S Rakshit, S Debnath, D Mondal\u00a0- arXiv preprint arXiv:1809.00340, 2018 - arxiv.org", "snippet": "\u2026 Deforestation in the Amazon rainforest has led to drastically reduced biodiversity, loss of \nhabitat\u2026 Image classification using deep learning can help speed up this process by removing the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=12671078963568788875&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:i0Vx4C632K8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12671078963568788875&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "An automated light trap to monitor moths (Lepidoptera) using computer vision-based tracking and deep learning", "title_link": "https://www.mdpi.com/951634", "publication_info": "K Bjerge, JB Nielsen, MV Sepstrup, F Helsing-Nielsen\u2026\u00a0- Sensors, 2021 - mdpi.com", "snippet": "\u2026 A computer vision algorithm referred to as Moth Classification and Counting (MCC), based \non deep learning analysis of the captured images, tracked and counted the number of insects \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7929094562109183529&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Kdb_fH7NCW4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7929094562109183529&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep-learning convolutional neural networks for scattered shrub detection with google earth imagery", "title_link": "https://arxiv.org/abs/1706.00917", "publication_info": "E Guirado, S Tabik, D Alcaraz-Segura\u2026\u00a0- arXiv preprint arXiv\u00a0\u2026, 2017 - arxiv.org", "snippet": "\u2026 , in land-use planning and biodiversity conservation. Developing \u2026 Recently, the deep learning \nConvolutional Neural Networks (\u2026 ing species of high biodiversity conservation interest. This \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11565463610418482018&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:YkuzkeDHgKAJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11565463610418482018&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "\u2026\u00a0extraction of phenotypic leaf traits of individual intact herbarium leaves from herbarium specimen images using deep learning based semantic segmentation", "title_link": "https://www.mdpi.com/1175124", "publication_info": "BR Hussein, OA Malik, WH Ong, JWF Slik\u00a0- Sensors, 2021 - mdpi.com", "snippet": "\u2026 intact leaves by combining deep learning and image processing \u2026 First, we applied aa deep \nlearning based semantic \u2026 utilization of these collections for various biodiversity studies [15]. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16239128002918087267&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Y_oHTOH4XOEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16239128002918087267&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Harnessing deep learning in ecology: An example predicting bark beetle outbreaks", "title_link": "https://www.frontiersin.org/articles/10.3389/fpls.2019.01327/full", "publication_info": "W Rammer, R Seidl\u00a0- Frontiers in plant science, 2019 - frontiersin.org", "snippet": "\u2026 Addressing current global challenges such as biodiversity loss, global change, and \u2026 \nDeep learning is a rapidly evolving branch of machine learning, yet has received only little \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14674006045589456801&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:oUdLk8CKpMsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14674006045589456801&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Integrating multi-sensors data for species distribution mapping using deep learning and envelope models", "title_link": "https://www.mdpi.com/2072-4292/13/16/3284", "publication_info": "A Anand, MK Pandey, PK Srivastava, A Gupta\u2026\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 The integration of ecological and atmospheric characteristics for biodiversity management \nis fundamental for long-term ecosystem conservation and drafting forest management \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17953685671559305477&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=CoEpduYAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=17953685671559305477&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automated conservation assessment of the orchid family with deep learning", "title_link": "https://conbio.onlinelibrary.wiley.com/doi/abs/10.1111/cobi.13616", "publication_info": "A Zizka, D Silvestro, P Vitt, TM Knight\u00a0- Conservation Biology, 2021 - Wiley Online Library", "snippet": "\u2026 Article impact statement: An automated conservation assessment with deep learning \u2026 \nPrioritizing the use of conservation resources is essential to counter the current global biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5616778938530526051&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=QMqWqrkAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=5616778938530526051&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Applications of deep learning in ornithology", "title_link": "https://biss.pensoft.net/article/27251/download/pdf/", "publication_info": "J Barry\u00a0- Biodiversity Information Science and Standards, 2018 - biss.pensoft.net", "snippet": "Earth\u2019s ecosystems are threatened by anthropogenic change, yet relatively little is known \nabout biodiversity across broad spatial (ie continent) and temporal (ie year-round) scales. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1424590671980106045&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:PZG1GaspxRMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1424590671980106045&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "The Practice of Deep Learning Methods in Biodiversity Information Collection", "title_link": "https://search.proquest.com/openview/6d7ba6020fae9065718ef217a22472bb/1?pq-origsite=gscholar&cbl=2049297", "publication_info": "J Wang, C Lin, C Bu, TY Xi, Z Wang\u2026\u00a0- Biodiversity Information\u00a0\u2026, 2019 - search.proquest.com", "snippet": "\u2026 In the field of biodiversity informatics, deep learning efforts are being applied in rapid \u2026 \nHowever, deep learning methods hold great potential for application in all aspects of biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=15118841373364145236&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=15118841373364145236&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for species identification of modern and fossil rodent molars", "title_link": "https://www.biorxiv.org/content/10.1101/2020.08.20.259176.abstract", "publication_info": "V Miele, G Dussert, T Cucchi, S Renaud\u00a0- bioRxiv, 2020 - biorxiv.org", "snippet": "\u2026 The deep-learning approach performed equally good as geometric morphometrics and, \u2026 \nDeep-learning methods may thus allow new insights on the biodiversity dynamics across \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15788764427603485576&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:iCOhLZj1HNsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15788764427603485576&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Using Deep Learning in Collection Management to Reduce the Taxonomist's Workload", "title_link": "https://search.proquest.com/openview/34d53ac276dc64b1bcf2cc2ed97f9214/1?pq-origsite=gscholar&cbl=2049297", "publication_info": "M Schermer, L Hogeweg\u2026\u00a0- Biodiversity Information\u00a0\u2026, 2018 - search.proquest.com", "snippet": "\u2026 identification in digitization workflows, using deep learning based image recognition. We \u2026 \nformed, limiting the speed of publication of this biodiversity information. The test case for image \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9745041077306764184&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:mKt1djpXPYcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9745041077306764184&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Extreme deep learning in biosecurity: the case of machine hearing for marine species identification", "title_link": "https://www.tandfonline.com/doi/abs/10.1080/24751839.2018.1501542", "publication_info": "K Demertzis, LS Iliadis, VD Anezakis\u00a0- Journal of Information and\u00a0\u2026, 2018 - Taylor & Francis", "snippet": "\u2026 rapidly worsening threat to natural biodiversity in Europe. They \u2026 biggest threat to local \nbiodiversity worldwide and is called \u2018bio-\u2026 The changes in biodiversity entail a change in relative \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17036241166643348874&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:isWpRRTjbOwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17036241166643348874&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A continental-scale assessment of density, size, distribution and historical trends of farm dams using deep learning convolutional neural networks", "title_link": "https://www.mdpi.com/965168", "publication_info": "ME Malerba, N Wright, PI Macreadie\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 also have disproportionally large effects on biodiversity and biogeochemical cycling, with \nimportant \u2026 Specifically, we trained a deep learning convolutional neural network (CNN) on high-\u2026", "cited_by": "https://scholar.google.com/scholar?cites=1209857596268234098&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ckVg3hJHyhAJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1209857596268234098&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Recognition of Endemic Bird Species Using Deep Learning Models", "title_link": "https://ieeexplore.ieee.org/abstract/document/9491098/", "publication_info": "YP Huang, H Basanta\u00a0- IEEE Access, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 pace is a significant threat to biodiversity worldwide. Thus, monitoring the distribution of \nspecies and identifying the elements that make up the biodiversity of a region are essential for \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9956244752247995919&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:D76WCtqvK4oJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9956244752247995919&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Deep learning for plant identification: how the web can compete with human experts", "title_link": "https://biss.pensoft.net/article/25637/download/pdf/", "publication_info": "H Go\u00ebau, A Joly, P Bonnet, M Lasseck\u2026\u00a0- Biodiversity\u00a0\u2026, 2018 - biss.pensoft.net", "snippet": "\u2026 in image classification with deep learning and several \u2026 In total, 9 deeplearning systems \nimplemented by 3 different \u2026 state-of-the-art deep learning models is now close to the most \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2392953908570629889&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ASc8xOZ6NSEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2392953908570629889&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Understanding deep learning in land use classification based on Sentinel-2 time series", "title_link": "https://www.nature.com/articles/s41598-020-74215-5", "publication_info": "M Campos-Taberner, FJ Garc\u00eda-Haro, B Mart\u00ednez\u2026\u00a0- Scientific reports, 2020 - nature.com", "snippet": "\u2026 allocate 5% of arable land to areas that improve biodiversity. To put this in context, in 2018 \na \u2026 achieved using machine learning algorithms, being deep learning (DL) the most accurate \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15716820120908093905&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:0Vlw8aBcHdoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15716820120908093905&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] A methodological proposal for collecting and creating macroscopic photograph collections of tropical woods with potential for use in deep learning", "title_link": "https://www.academia.edu/download/62919654/A_Methodological_Proposal_for_Collecting_and_Creating_Macroscopic_Photograph_Collections_of_Tropical_Woods20200411-8576-1p7eqd7.pdf", "publication_info": "E Mata-Montero, JC Valverde\u2026\u00a0- Biodiversity\u00a0\u2026, 2018 - academia.edu", "snippet": "\u2026 Deep learning techniques have recently been used to \u2026 As a first step in the application of \ndeep learning techniques, we \u2026 the primary data necessary for deep learning applications. Unlike \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15463194942822098632&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:yCaHe99NmNYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15463194942822098632&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Assessment of deep learning techniques for land use land cover classification in southern new Caledonia", "title_link": "https://www.mdpi.com/2072-4292/13/12/2257", "publication_info": "G Rousset, M Despinoy, K Schindler, M Mangeas\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 , a biodiversity \u2026 , Deep Learning has recently stood out as a particularly effective framework \nfor automatic image interpretation [12]. Given large amounts of training data, Deep Learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8677556345028830992&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:EGfhJ4XfbHgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8677556345028830992&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Plant identification: experts vs. machines in the era of deep learning", "title_link": "https://link.springer.com/chapter/10.1007/978-3-319-76445-0_8", "publication_info": "P Bonnet, H Go\u00ebau, ST Hang, M Lasseck\u2026\u00a0- \u2026\u00a0& biodiversity\u00a0\u2026, 2018 - Springer", "snippet": "\u2026 to the recent advances in deep learning. The next big question \u2026 In total, nine deep-learning \nsystems implemented by three \u2026 state-of-the-art deep learning models is now close to the most \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8405593191309858505&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:yVZ3BnmqpnQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8405593191309858505&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning applications to automate phenotypic measurements on biodiversity datasets", "title_link": "https://etheses.whiterose.ac.uk/28780/", "publication_info": "Y He - 2020 - etheses.whiterose.ac.uk", "snippet": "\u2026 Deep learning is the state-of-the-art for many computer vision tasks. Deep learning models \ncan \u2026 To what extent deep learning can help to improve the measurement process on digitised \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=13213036793190333239&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=13213036793190333239&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Columnar cactus recognition in aerial images using a deep learning approach", "title_link": "https://www.sciencedirect.com/science/article/pii/S1574954119300895", "publication_info": "E L\u00f3pez-Jim\u00e9nez, JI Vasquez-Gomez\u2026\u00a0- Ecological\u00a0\u2026, 2019 - Elsevier", "snippet": "\u2026 This unique area has wide biodiversity including several endemic plants. Unfortunately, \u2026 \nIn this work, we present a deep learning based approach for columnar cactus recognition, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3037343346387660087&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Ny1VVq7PJioJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3037343346387660087&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Applications of deep convolutional neural networks to digitized natural history collections", "title_link": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5680669/", "publication_info": "E Schuettpelz, PB Frandsen, RB Dikow\u2026\u00a0- Biodiversity data\u00a0\u2026, 2017 - ncbi.nlm.nih.gov", "snippet": "\u2026 Therefore, to assess the utility of using deep learning to identify mercury-contaminated \nspecimens, we manually assembled a set of 7,777 unstained (https://doi.org/10.6084/m9.figshare.\u2026", "cited_by": "https://scholar.google.com/scholar?cites=10993762125669105735&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:R4Cm5WewkZgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10993762125669105735&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep learning and citizen science enable automated plant trait predictions from photographs", "title_link": "https://www.nature.com/articles/s41598-021-95616-0", "publication_info": "C Schiller, S Schmidtlein, C Boonman\u2026\u00a0- Scientific Reports, 2021 - nature.com", "snippet": "\u2026 imposes a threat on global biodiversity 1 . The loss of biodiversity inevitably leads to a loss of \n\u2026 Convolutional Neural Networks (CNN), a deep learning-oriented computer vision technique\u2026", "cited_by": "https://scholar.google.com/scholar?cites=16980984731487926362&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Wnir6KSTqOsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16980984731487926362&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Large-scale plant classification with deep neural networks", "title_link": "https://dl.acm.org/doi/abs/10.1145/3075564.3075590", "publication_info": "I Heredia\u00a0- Proceedings of the Computing Frontiers Conference, 2017 - dl.acm.org", "snippet": "\u2026 deep learning techniques for plant classification and its usage for citizen science in large-scale \nbiodiversity \u2026 tusfera) which in turn can share their data with biodiversity portals like GBIF. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17335400590463979625&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:adCzef22k_AJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17335400590463979625&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Semantic segmentation of tree-canopy in urban environment with pixel-wise deep learning", "title_link": "https://www.mdpi.com/2072-4292/13/16/3054", "publication_info": "JAC Martins, K Nogueira, LP Osco, FDG Gomes\u2026\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 leading to ecosystem stress and biodiversity losses [13]. In \u2026 environment, such as urban \nbiodiversity loss and changes in the \u2026 life, city hydrodynamics, and biodiversity by preserving and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2987192235404022367&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:X9IP44KjdCkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2987192235404022367&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Predicting animal behaviour using deep learning: GPS data alone accurately predict diving in seabirds", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.12926", "publication_info": "E Browning, M Bolton, E Owen, A Shoji\u2026\u00a0- Methods in Ecology\u00a0\u2026, 2018 - Wiley Online Library", "snippet": "\u2026 To prevent further global declines in biodiversity, identifying \u2026 from 108 individuals by training \ndeep learning models to predict \u2026 ability of these supervised deep learning models over other \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16032955641722371548&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=hWPAzU0AAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=16032955641722371548&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Tree cover estimation in global drylands from space using deep learning", "title_link": "https://www.mdpi.com/622602", "publication_info": "E Guirado, D Alcaraz-Segura, J Cabello\u2026\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "Accurate tree cover mapping is of paramount importance in many fields, from biodiversity \nconservation to carbon stock estimation, ecohydrology, erosion control, or Earth system \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3017341195303131313&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:sRgyoNS_3ykJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3017341195303131313&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning neural network for identification of bird species", "title_link": "https://link.springer.com/chapter/10.1007/978-981-13-7150-9_31", "publication_info": "SK Pillai, MM Raghuwanshi, U Shrawankar\u00a0- Computing and Network\u00a0\u2026, 2019 - Springer", "snippet": "\u2026 Biodiversity is declining relentlessly \u2026 biodiversity preservation. In this way, quick and exact \nplant distinguishing proof is essential for viable investigation and administration of biodiversity. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9443746529079241176&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:2KmY3m7tDoMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9443746529079241176&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automatic whale counting in satellite images with deep learning", "title_link": "https://www.biorxiv.org/content/10.1101/443671.abstract", "publication_info": "E Guirado, S Tabik, ML Rivas, D Alcaraz-Segura\u2026\u00a0- BioRxiv, 2018 - biorxiv.org", "snippet": "\u2026 marine biodiversity protection against global change (66). In addition, since deep learning is \n\u2026 The compromise with biodiversity conservation from corporations such as Google, Microsoft\u2026", "cited_by": "https://scholar.google.com/scholar?cites=1298795103501811404&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=2nE7TNgAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=1298795103501811404&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep-learning Versus OBIA for Scattered Shrub Detection with Google Earth Imagery: Ziziphus lotus as Case Study", "title_link": "https://www.mdpi.com/2072-4292/9/12/1220", "publication_info": "E Guirado, S Tabik, D Alcaraz-Segura, J Cabello\u2026\u00a0- Remote Sensing, 2017 - mdpi.com", "snippet": "\u2026 , eg, in land-use planning and biodiversity conservation. Developing such maps has been \n\u2026 Recently, deep learning Convolutional Neural Networks (CNNs) have shown outstanding \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9813607604754582052&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=qycjmEoAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=9813607604754582052&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Vegetation detection using deep learning and conventional methods", "title_link": "https://www.mdpi.com/788942", "publication_info": "B Ayhan, C Kwan, B Budavari, L Kwan, Y Lu, D Perez\u2026\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "\u2026 planning, autonomous navigation, drone mapping, biodiversity conservation, etc. Conventional \n\u2026 of deep learning and conventional methods for vegetation detection. Two deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=12941461480455002121&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=HsFztiUAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=12941461480455002121&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] A deep learning based platform for automatic species identification to scale-up biodiversity monitoring", "title_link": "https://www.researchgate.net/profile/Sheetabh-Gaurav/publication/338293326_A_deep_learning_based_platform_for_automatic_species_identification_to_scale-up_biodiversity_monitoring/links/5f912e37a6fdccfd7b746a53/A-deep-learning-based-platform-for-automatic-species-identification-to-scale-up-biodiversity-monitoring.pdf", "publication_info": "S Gaurav, AK Jha, S Saran - researchgate.net", "snippet": "\u2026 Biodiversity monitoring is quite essential as various flora and \u2026 With the recent advancements \nin the field of deep learning [1], a subset of \u2026 In the present work, a deep learning algorithm, ie \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:jyohZljni2EJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[BOOK][B] Smart Agriculture: Emerging Pedagogies of Deep Learning, Machine Learning and Internet of Things", "title_link": "https://books.google.com/books?hl=en&lr=&id=1m8OEAAAQBAJ&oi=fnd&pg=PP1&dq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&ots=6GBOUCbEAX&sig=SaQ6HNohDv68hr0dygKoH1zEQm0", "publication_info": "GS Patel, A Rai, NN Das, RP Singh - 2021 - books.google.com", "snippet": "\u2026 through Artificial Intelligence, deep learning and Internet of \u2026 chain management, food \navailability, biodiversity, farmers\u2019 decision-\u2026 of Machine Learning, Deep Learning, Big Data and IoT \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10982253609953172818&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Up2CxnjNaJgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10982253609953172818&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Evaluation of deep learning techniques for deforestation detection in the Amazon forest", "title_link": "https://www.researchgate.net/profile/Mabel-Ortega-3/publication/335843495_EVALUATION_OF_DEEP_LEARNING_TECHNIQUES_FOR_DEFORESTATION_DETECTION_IN_THE_AMAZON_FOREST/links/5d977d0b299bf1c363f8cfb4/EVALUATION-OF-DEEP-LEARNING-TECHNIQUES-FOR-DEFORESTATION-DETECTION-IN-THE-AMAZON-FOREST.pdf", "publication_info": "MX Ortega, JD Bermudez, PN Happ\u2026\u00a0- ISPRS Annals of the\u00a0\u2026, 2019 - researchgate.net", "snippet": "\u2026 Deforestation is one of the main causes of biodiversity reduction, climate change among \nother \u2026 The Deep Learning-based approaches clearly outperformed the SVM baseline in our \u2026", "cited_by": "https://scholar.google.com/scholar?cites=12034058720801564456&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:KKeRu6WQAacJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12034058720801564456&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] A novel deep learning based approach for seed image classification and retrieval", "title_link": "https://www.sciencedirect.com/science/article/pii/S0168169921002866", "publication_info": "A Loddo, M Loddo, C Di Ruberto\u00a0- Computers and Electronics in\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 has become essential to preserve biodiversity. This is why \u2026 families or species through deep \nlearning techniques. SeedNet, a \u2026 The retrieval problem with the deep learning approach was \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17139797185351643977&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:SfMfw7rK3O0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17139797185351643977&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Improving acoustic monitoring of biodiversity using deep learning-based source separation algorithms", "title_link": "https://scholar.archive.org/work/oko7eqz74neavj42us3plag74a/access/wayback/https://www.db-thueringen.de/servlets/MCRFileNodeServlet/dbt_derivate_00043950/Tuanmu_S1.2_IECI2018.pdf", "publication_info": "THH Lin, MN Tuanmu, JCC Huang, CY Lee, Y Tsao - scholar.archive.org", "snippet": "Improving acoustic monitoring of biodiversity using deep learning-based source separation \nalgorithms \u2026 Biodiversity Research Center, Academia Sinica \u2026 Is it possible to evaluate\u00a0\u2026", "cited_by": "https://scholar.google.com/scholar?cluster=4024653589673238590&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=4024653589673238590&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Machine learning as a service for DiSSCo's digital specimen architecture", "title_link": "https://orca.cardiff.ac.uk/id/eprint/144389", "publication_info": "J Grieb, C Weiland, A Hardisty, W Addink, S Islam\u2026 - 2021 - orca.cardiff.ac.uk", "snippet": "\u2026 Younis S, Schmidt M, Weiland C, Dressler S, Seeger B, Hickler T (2020) Detection and \nannotation of plant organs from digitised herbarium scans using deep learning. Biodiversity Data \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3964480695134472814&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:bkpiADCqBDcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3964480695134472814&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Bag of Features (BoF) Based Deep Learning Framework for Bleached Corals Detection", "title_link": "https://www.mdpi.com/1303030", "publication_info": "S Jamil, MU Rahman, A Haider\u00a0- Big Data and Cognitive Computing, 2021 - mdpi.com", "snippet": "\u2026 on the planet because they help to maintain biodiversity and the life cycles of so many \nmarine \u2026 The coral reef has a vital role in preserving biodiversity, ceasing coastal erosion, and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13448967093870102167&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:l4YL8lBUpLoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13448967093870102167&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Hierarchical mapping of Brazilian Savanna (Cerrado) physiognomies based on deep learning", "title_link": "https://www.spiedigitallibrary.org/journals/journal-of-applied-remote-sensing/volume-15/issue-4/044504/Hierarchical-mapping-of-Brazilian-Savanna-Cerrado-physiognomies-based-on-deep/10.1117/1.JRS.15.044504.short", "publication_info": "AK Neves, TS K\u00f6rting, LMG Fonseca\u2026\u00a0- Journal of Applied\u00a0\u2026, 2021 - spiedigitallibrary.org", "snippet": "\u2026 Especially in tropical regions, they are rich in biodiversity 1 \u2026 a global hotspot for biodiversity \nconservation, containing \u2026 ie, specific regions established to protect biodiversity, water bodies, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5613261445554265148&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:PFyoXYtP5k0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5613261445554265148&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep Learning and Earth Observation to Support the Sustainable Development Goals", "title_link": "https://arxiv.org/abs/2112.11367", "publication_info": "C Persello, JD Wegner, R H\u00e4nsch, D Tuia\u2026\u00a0- arXiv preprint arXiv\u00a0\u2026, 2021 - arxiv.org", "snippet": "\u2026 This paper reviews current deep learning approaches for \u2026 the rapid development of deep \nlearning in Earth observation. \u2026 , and 5) preserve biodiversity. Important societal, economic and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14957177947953314368&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=p3iJiLIAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=14957177947953314368&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Fish classification using DNA barcode sequences through deep learning method", "title_link": "https://www.mdpi.com/1252942", "publication_info": "L Jin, J Yu, X Yuan, X Du\u00a0- Symmetry, 2021 - mdpi.com", "snippet": "\u2026 biodiversity and fishery resources management, as well as an important part of biodiversity. \nAs a \u2026 barcode sequences, we introduce a deep learning model to extract useful features and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13291477031310719922&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:svuJT_DPdLgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13291477031310719922&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Using deep learning for image-based plant disease detection", "title_link": "https://www.frontiersin.org/articles/10.3389/fpls.2016.01419/full", "publication_info": "SP Mohanty, DP Hughes, M Salath\u00e9\u00a0- Frontiers in plant science, 2016 - frontiersin.org", "snippet": "\u2026 Here, we demonstrate the technical feasibility using a deep learning approach utilizing \n54,306 images of 14 crop species with 26 diseases (or healthy) made openly available through \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13647028329232773843&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:07Kc2_X7Y70J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13647028329232773843&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Investigation of different CNN-based models for improved bird sound classification", "title_link": "https://ieeexplore.ieee.org/abstract/document/8922774/", "publication_info": "J Xie, K Hu, M Zhu, J Yu, Q Zhu\u00a0- IEEE Access, 2019 - ieeexplore.ieee.org", "snippet": "\u2026 further protecting biodiversity. Recent advances in acoustic sensor networks and deep learning \n\u2026 Specifically, we not only use the same deep learning architecture with different inputs but \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6091579183061974467&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:w72SD_6iiVQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6091579183061974467&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Development of spectral-phenological features for deep learning to understand Spartina alterniflora invasion", "title_link": "https://www.sciencedirect.com/science/article/pii/S0034425720301152", "publication_info": "J Tian, L Wang, D Yin, X Li, C Diao, H Gong\u2026\u00a0- Remote Sensing of\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 to the ecosystem and biodiversity as well as economic losses \u2026 performance of the latest deep \nlearning method as opposed to \u2026 study area; (2) deep learning, compared to SVM, presented \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11938250585430710674&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=UhO8GOEAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=11938250585430710674&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Plant identification based on noisy web data: the amazing performance of deep learning (LifeCLEF 2017)", "title_link": "https://hal.archives-ouvertes.fr/hal-01629183/document", "publication_info": "H Goeau, P Bonnet, A Joly\u00a0- CLEF: Conference and Labs of\u00a0\u2026, 2017 - hal.archives-ouvertes.fr", "snippet": "\u2026 Nowadays, such ambitious systems are enabled thanks to the conjunction of the dazzling \nrecent progress in image classification with deep learning and several outstanding \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4760912283445089224&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:yNOJVX8oEkIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4760912283445089224&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Deep learning for wildlife conservation and restoration efforts", "title_link": "https://www.climatechange.ai/papers/icml2019/31/paper.pdf", "publication_info": "C Duhart, G Dublon, B Mayton\u2026\u00a0- \u2026\u00a0on Machine Learning\u00a0\u2026, 2019 - climatechange.ai", "snippet": "\u2026 Automatic wildlife sensing is an urgent requirement to track biodiversity losses on Earth. \nRecent im\u2026 Tidzam\u2019 is a Deep Learning framework for wildlife detection, identification, and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4198265724482374747&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:W0x43G48QzoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4198265724482374747&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Trade-off between deep learning for species identification and inference about predator-prey co-occurrence: Reproducible R workflow integrating models in computer\u00a0\u2026", "title_link": "https://arxiv.org/abs/2108.11509", "publication_info": "O Gimenez, M Kervellec, JB Fanjul, A Chaine\u2026\u00a0- arXiv preprint arXiv\u00a0\u2026, 2021 - arxiv.org", "snippet": "\u2026 We illustrate deep learning for the identification of animal species on images collected with \n\u2026 deep learning and our ability to properly address key ecological questions with biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10238434392025394555&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:e-3QgNU5Fo4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10238434392025394555&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Evaluation of Deep Learning Techniques for Deforestation Detection in the Brazilian Amazon and Cerrado Biomes From Remote Sensing Imagery.", "title_link": "https://www.mdpi.com/2072-4292/12/6/910/pdf?version=1584613231", "publication_info": "MO Adarme, RQ Feitosa, PN Happ, CA De Almeida\u2026\u00a0- Remote. Sens., 2020 - mdpi.com", "snippet": "\u2026 to climate change and biodiversity reduction. Therefore, the \u2026 , the present work evaluates \nDeep Learning-based strategies \u2026 The strategies based on Deep Learning achieved the best \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4719195103243835663&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=BQCj2YoAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.comhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=GSSearch&SrcAuth=Scholar&DestApp=WOS_CPL&DestLinkType=CitingArticles&UT=000526820600012&SrcURL=https://scholar.google.com/&SrcDesc=Back+to+Google+Scholar&GSPage=TC"}, {"title": "A Deep Learning algorithm for accurate and fast identification of coral reef fishes in underwater videos", "title_link": "https://scholar.archive.org/work/4lhs2mzsb5etphkamwtk7ggovq/access/wayback/https://peerj.com/preprints/26818.pdf", "publication_info": "S Villon, D Mouillot, M Chaumont, ES Darling\u2026\u00a0- PeerJ\u00a0\u2026, 2018 - scholar.archive.org", "snippet": "\u2026 biodiversity\u2026 Deep Learning methods can thus perform efficient fish identification on underwater \npictures which pave the way to new video-based protocols for monitoring fish biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2288060086154636865&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:QS7_k4bSwB8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2288060086154636865&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Taxonomic classification of ants (Formicidae) from images using deep learning", "title_link": "https://www.biorxiv.org/content/10.1101/407452.abstract", "publication_info": "MJA Boer, RA Vos\u00a0- bioRxiv, 2018 - biorxiv.org", "snippet": "\u2026 species richness, ecosystem health, and biodiversity, but ant species identification is complex \n\u2026 Here we propose deep learning (in the form of a convolutional neural network (CNN)) to \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3722953684751596688&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:kLzZtqaWqjMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3722953684751596688&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Pollen analysis using multispectral imaging flow cytometry and deep learning", "title_link": "https://nph.onlinelibrary.wiley.com/doi/abs/10.1111/nph.16882", "publication_info": "S Dunker, E Motivans, D Rakosy, D Boho\u2026\u00a0- New\u00a0\u2026, 2021 - Wiley Online Library", "snippet": "\u2026 In this study, we present a new method for pollen analysis using multispectral imaging flow \ncytometry in combination with deep learning. We demonstrate that our method allows fast \u2026", "cited_by": "https://scholar.google.com/scholar?cites=472385031782864745&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:aRehAK8_jgYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=472385031782864745&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Coral reef fish detection and recognition in underwater videos by supervised machine learning: Comparison between Deep Learning and HOG+ SVM methods", "title_link": "https://link.springer.com/chapter/10.1007/978-3-319-48680-2_15", "publication_info": "S Villon, M Chaumont, G Subsol, S Vill\u00e9ger\u2026\u00a0- \u2026\u00a0on Advanced Concepts\u00a0\u2026, 2016 - Springer", "snippet": "\u2026 Quantifying human impact on fish biodiversity in order to propose solutions to preserve \u2026 \nMoreover, the use of fishing, even for survey purposes, impacts the studied biodiversity. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5979343351578985676&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=vLK2CbwAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=5979343351578985676&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "UAV-based hyperspectral images and monitoring of canopy tree diversity", "title_link": "https://www.biodiversity-science.net/EN/Y2021/V29/I5/647", "publication_info": "Y Xu, C Zhang, R Jiang, Z Wang, M Zhu\u2026\u00a0- Biodiversity\u00a0\u2026, 2021 - biodiversity-science.net", "snippet": "\u2026 However, updating these changes in biodiversity cannot be \u2026 of forest canopy for biodiversity \nmonitoring and conservation, \u2026 image processing technology with deep learning. We use the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2541110972000367115&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:C_LtNPfWQyMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2541110972000367115&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] A Pipeline for Deep Learning with Specimen Images in IDigBio-Applying and Generalizing an Examination of Mercury Use in Preparing Herbarium Specimens", "title_link": "https://biss.pensoft.net/article/25699/download/pdf/", "publication_info": "M Collins, G Yeole, P Frandsen, R Dikow\u2026\u00a0- Biodiversity\u00a0\u2026, 2018 - biss.pensoft.net", "snippet": "\u2026 We have placed a Jupyter notebook server in front of this architecture which provides an \neasy environment with deep learning libraries for Python already loaded for end users to write \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2168870563336085596&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:XOByQ0lgGR4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2168870563336085596&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Camera Assisted Roadside Monitoring for Invasive Alien Plant Species Using Deep Learning", "title_link": "https://www.mdpi.com/1268428", "publication_info": "M Dyrmann, AK Mortensen, L Linneberg, TT H\u00f8ye\u2026\u00a0- Sensors, 2021 - mdpi.com", "snippet": "\u2026 IAPS are considered to be a major driver of biodiversity loss. Invasive species are among \nthe top five threats to biodiversity worldwide [3]. They pose a threat to native species, their \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14731145430988024439&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:d-qodLiKb8wJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14731145430988024439&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] An alternative approach for mapping burn scars using Landsat imagery, Google Earth Engine, and Deep Learning in the Brazilian Savanna", "title_link": "https://www.sciencedirect.com/science/article/pii/S2352938521000082", "publication_info": "VLS Arruda, VJ Piontekowski, A Alencar\u2026\u00a0- Remote Sensing\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 and has one of the highest levels of biodiversity in the world. Wildfires have historically \u2026 \nin Brazil, using Landsat imagery and Deep Learning algorithm, implemented on the Google \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17230192709164367029&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:tXxEwfrwHe8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17230192709164367029&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automatic windthrow detection using very-high-resolution satellite imagery and deep learning", "title_link": "https://www.mdpi.com/682138", "publication_info": "DE Kislov, KA Korznikov\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "\u2026 They cause changes in biodiversity, impact on forest ecosystems at different spatial scales, \n\u2026 to by a common term\u2014deep learning. Deep learning provides powerful algorithms for the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11213035772855696441&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ObzPTqC0nJsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11213035772855696441&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Counting wildebeest from space using deep learning", "title_link": "http://essay.utwente.nl/88785/1/s2278308%20-%20Thesis%20Zijing.pdf", "publication_info": "Z Wu - 2021 - essay.utwente.nl", "snippet": "\u2026 face of unprecedented biodiversity loss worldwide. Deep learning techniques combined with \n\u2026 In conclusion, this study demonstrates an effective and efficient U-Net deep learning model \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:T2oguI0JxvYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[HTML][HTML] Reconstruction of damaged herbarium leaves using deep learning techniques for improving classification accuracy", "title_link": "https://www.sciencedirect.com/science/article/pii/S1574954121000340", "publication_info": "BR Hussein, OA Malik, WH Ong, JWF Slik\u00a0- Ecological Informatics, 2021 - Elsevier", "snippet": "\u2026 In this study, deep learning techniques have been proposed as a tool for reconstructing the \ndamaged \u2026 This work evidently suggests that deep learning techniques can be utilized for \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8891153504091039689&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:yefQLgG5Y3sJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8891153504091039689&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Country-wide retrieval of forest structure from optical and SAR satellite imagery with Bayesian deep learning", "title_link": "https://arxiv.org/abs/2111.13154", "publication_info": "A Becker, S Russo, S Puliti, N Lang, K Schindler\u2026\u00a0- arXiv preprint arXiv\u00a0\u2026, 2021 - arxiv.org", "snippet": "\u2026 for addressing challenges like biodiversity loss and climate \u2026 In this work, we propose a \nBayesian deep learning approach \u2026 first to propose a Bayesian deep learning approach so as to \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9184806732252321026&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=bVZtKsQAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=9184806732252321026&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Accelerating the automated detection, counting and measurements of reproductive organs in herbarium collections in the era of deep learning", "title_link": "https://agritrop.cirad.fr/598381/1/BISS_article_37341.pdf", "publication_info": "A Mora-Fallas, H Go\u00ebau, SJ Mazer, N Love\u2026 - 2019 - agritrop.cirad.fr", "snippet": "\u2026 Deep learning technologies can dramatically accelerate the extraction of such basic \ninformation by automating the routines of organ identification, counts and measurements, thereby \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13900144863401937993&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=tfYEbzEAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=13900144863401937993&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Counting sea lions and elephants from aerial photography using deep learning with density maps", "title_link": "https://animalbiotelemetry.biomedcentral.com/articles/10.1186/s40317-021-00247-x", "publication_info": "C Padubidri, A Kamilaris\u2026\u00a0- Animal\u00a0\u2026, 2021 - animalbiotelemetry.biomedcentral\u00a0\u2026", "snippet": "\u2026 and to monitor their populations in relation to biodiversity and maintain balance among species. \nOut of \u2026 In this paper, we propose the use of computer vision, through deep learning (DL) \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1295318748252816150&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:FkOD5Inl-REJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1295318748252816150&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Going deeper in the automated identification of Herbarium specimens", "title_link": "https://bmcecolevol.biomedcentral.com/articles/10.1186/s12862-017-1014-z", "publication_info": "J Carranza-Rojas, H Goeau\u2026\u00a0- BMC\u00a0\u2026, 2017 - bmcecolevol.biomedcentral.com", "snippet": "\u2026 deep learning to analyze a big dataset with thousands of species from herbaria. Results show \nthe potential of Deep Learning \u2026 So far, most of the biodiversity informatics research related \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13047112984150723570&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:8suw7CGoELUJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13047112984150723570&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Automated image-based taxon identification using deep learning and citizen-science contributions", "title_link": "https://www.diva-portal.org/smash/record.jsf?pid=diva2:1522250", "publication_info": "M Valan - 2021 - diva-portal.org", "snippet": "\u2026 The sixth mass extinction is well under way, with biodiversity disappearing at unprecedented \nrates in \u2026 Unfortunately, these so-called deep learning systems often requiresubstantial \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8303568855326925834&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:CiTCNeEzPHMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Species Distribution Modelling Using Deep Learning.", "title_link": "https://go.gale.com/ps/i.do?id=GALE%7CA646493909&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=25350897&p=AONE&sw=w", "publication_info": "RA Vos, M Rademaker, L Hogeweg\u00a0- Biodiversity Information Science\u00a0\u2026, 2019 - go.gale.com", "snippet": "\u2026 of workflows to apply deep learning to species distribution \u2026 of deep learning in web \nservice infrastructures to analyze the growing corpus of species occurrence data in biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=1390446598595666912&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=1390446598595666912&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Evaluation of Deep Learning techniques to address environmental issues", "title_link": "https://oa.upm.es/id/eprint/64923", "publication_info": "L Mata Aguilar - 2020 - oa.upm.es", "snippet": "\u2026 for biodiversity, climate change and human needs. One of the main causes of biodiversity \u2026 \nIn this study, the usefulness of deep learning (DL) techniques is evaluated along with the \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comhttps://scholar.googleusercontent.com/scholar?q=cache:wqxfzorjKAMJ:scholar.google.com/+biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Deep learning for plant species classification survey", "title_link": "https://ieeexplore.ieee.org/abstract/document/9036796/", "publication_info": "PGM Sobha, PA Thomas\u00a0- 2019 International Conference on\u00a0\u2026, 2019 - ieeexplore.ieee.org", "snippet": "\u2026 Abstract\u2014\u200bProtection of biodiversity is quite essential and for this purpose we should know \n\u2026 Machine learning and deep learning play an important role in this matter. The deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5064199132047510550&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:FoyIgUemR0YJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Forest damage assessment using deep learning on high resolution remote sensing data", "title_link": "https://www.mdpi.com/519726", "publication_info": "ZM Hamdi, M Brandmeier, C Straub\u00a0- Remote Sensing, 2019 - mdpi.com", "snippet": "\u2026 Storms can cause significant damage to forest areas, affecting biodiversity and infrastructure \n\u2026 Our results and the provided automatic workflow highlight the potential of deep learning on \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16471066006994212237&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:jdXmEkT7lOQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16471066006994212237&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Identification of tree species in Japanese forests based on aerial photography and deep learning", "title_link": "https://link.springer.com/chapter/10.1007/978-3-030-61969-5_18", "publication_info": "S Kentsch, S Karatsiolis, A Kamilaris\u2026\u00a0- Advances and New\u00a0\u2026, 2021 - Springer", "snippet": "\u2026 their significant role in climate regulation, biodiversity, soil erosion and disaster prevention \u2026 \nmixed forests using UAV images and deep learning in two different mixed forest types: a black \u2026", "cited_by": "https://scholar.google.com/scholar?cites=127725314049474104&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:OH6-FH_FxQEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=127725314049474104&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Application of machine learning in ocean data", "title_link": "https://link.springer.com/article/10.1007/s00530-020-00733-x", "publication_info": "R Lou, Z Lv, S Dang, T Su, X Li\u00a0- Multimedia Systems, 2021 - Springer", "snippet": "\u2026 deep learning has also promoted the current upsurge in machine learning research. For \nexample, in 2012, the Hinton research team used deep learning \u2026 Biodiversity is a broad concept \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11461845845516508031&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:f1tMrBGoEJ8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11461845845516508031&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Marine Data Prediction: An Evaluation of Machine Learning, Deep Learning, and Statistical Predictive Models", "title_link": "https://www.hindawi.com/journals/cin/2021/8551167/", "publication_info": "A Ali, A Fathalla, A Salah, M Bekhit\u2026\u00a0- Computational\u00a0\u2026, 2021 - hindawi.com", "snippet": "\u2026 data such as sea surface temperature (SST) and Significant Wave Height (SWH) is a vital \ntask in a variety of disciplines, including marine activities, deep-sea, and marine biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2371830649429097823&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=_XvCnrcAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=2371830649429097823&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "The necessity, promise and challenge of automated biodiversity surveys", "title_link": "https://www.cambridge.org/core/journals/environmental-conservation/article/necessity-promise-and-challenge-of-automated-biodiversity-surveys/0F902C0A1E02BE2369F9C802C26FA083", "publication_info": "J Kitzes, L Schricker\u00a0- Environmental Conservation, 2019 - cambridge.org", "snippet": "\u2026 in automated biodiversity survey \u2026 of biodiversity data \u2013 point occurrence records \u2013 that are \nfrequently produced by citizen science projects, museum records and systematic biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6207116805208499933&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:3WbP_dgbJFYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6207116805208499933&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A deep active learning system for species identification and counting in camera trap images", "title_link": "https://ui.adsabs.harvard.edu/abs/2019arXiv191009716S/abstract", "publication_info": "M Sadegh Norouzzadeh, D Morris, S Beery\u2026\u00a0- arXiv e\u00a0\u2026, 2019 - ui.adsabs.harvard.edu", "snippet": "\u2026 -based biodiversity surveys, and recent studies have harnessed deep learning techniques \nfor \u2026 ecosystems have struggled to adopt deep learning methods because image classification \u2026", "cited_by": "https://scholar.google.com/scholar?cites=12265163886141066985&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:6U5jIZKdNqoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Deep learning approaches for the mapping of tree species diversity in a tropical wetland using airborne LiDAR and high-spatial-resolution remote sensing images", "title_link": "https://www.mdpi.com/577230", "publication_info": "Y Sun, J Huang, Z Ao, D Lao, Q Xin\u00a0- Forests, 2019 - mdpi.com", "snippet": "\u2026 for biodiversity assessments in forests and demonstrated the potential of cost-effective VHR \nimages in biodiversity \u2026 Deep learning approaches have become powerful tools for feature \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13617044746460863367&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:hxtm-wx2-bwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13617044746460863367&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "MaskIt: Masking for efficient utilization of incomplete public datasets for training deep learning models", "title_link": "https://arxiv.org/abs/2006.12004", "publication_info": "A Kariryaa\u00a0- arXiv preprint arXiv:2006.12004, 2020 - arxiv.org", "snippet": "\u2026 for monitoring biodiversity, where the data is populated by deep learning pipelines and \u2026 \n, extinction of species, and continuously shrinking biodiversity. This notion is also shared by \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8975758860273859033&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:2TkwuCBNkHwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8975758860273859033&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Hidden biases in automated image-based plant identification", "title_link": "https://ieeexplore.ieee.org/abstract/document/8464187/", "publication_info": "J Carranza-Rojas, E Mata-Montero\u2026\u00a0- 2018 IEEE International\u00a0\u2026, 2018 - ieeexplore.ieee.org", "snippet": "\u2026 biodiversity conservation actions such as biodiversity invento\u2026 Because deep learning has \ndemonstrated impressive results \u2026 other hand, newer deep learning approaches used in events \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3812962379713717486&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:7qTDGBVd6jQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "A comparison of deep learning and citizen science techniques for counting wildlife in aerial survey images", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13165", "publication_info": "CJ Torney, DJ Lloyd\u2010Jones\u2026\u00a0- Methods in Ecology\u00a0\u2026, 2019 - Wiley Online Library", "snippet": "\u2026 Our results show that deep learning algorithms are now at a state where they can legitimately \nreplace manual counters and remove a large burden from conservation organisations. The \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13251910972435152787&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:kz8ZW9E-6LcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13251910972435152787&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Acoustic auto-encoders for biodiversity assessment", "title_link": "https://www.sciencedirect.com/science/article/pii/S1574954121000285", "publication_info": "B Rowe, P Eichinski, J Zhang, P Roe\u00a0- Ecological Informatics, 2021 - Elsevier", "snippet": "\u2026 For deep learning tasks you often start from a point of labelling training your data. However \nthis can be slow and problematic. It can be useful to have a general representation for \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17960650048813418212&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:5EagTg8MQfkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17960650048813418212&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Forest Conservation with Deep Learning: A Deeper Understanding of Human Geography around the Betampona Nature Reserve, Madagascar", "title_link": "https://www.mdpi.com/1256820", "publication_info": "G Cota, V Sagan, M Maimaitijiang, K Freeman\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 to be one of eight biodiversity hotspots across the globe [3]. It is \u2026 of tropical forests and \nbiodiversity at the global scale for \u2026 animal species also threaten the biodiversity within the BNR [9]. \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:sBLfuPFGb1QJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=6084159625603519152&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6084159625603519152&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Domain Adaptation and Active Learning for Fine-Grained Recognition in the Field of Biodiversity", "title_link": "https://arxiv.org/abs/2110.11778", "publication_info": "B Gruner, M K\u00f6rschens, B Barz, J Denzler\u00a0- arXiv preprint arXiv\u00a0\u2026, 2021 - arxiv.org", "snippet": "\u2026 Deep-learning methods offer unsurpassed recognition performance in a wide range of \u2026 \ncan be used for fine-grained recognition in a biodiversity context to learn a real-world classifier \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:LiVQxfue228J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=8060210762293978414&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8060210762293978414&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Performance of MobileNetV3 Transfer Learning on Handheld Device-based Real-Time Tree Species Identification", "title_link": "https://ieeexplore.ieee.org/abstract/document/9594222/", "publication_info": "A Hussain, B Barua, A Osman\u2026\u00a0- \u2026\u00a0on Automation and\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 forest health monitoring and biodiversity conservation. Current deep learning-based mobile \n\u2026 research to support forest health monitoring and biodiversity conservation [2]. Many tasks, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10234962582160163065&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:-UASxz3kCY4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10234962582160163065&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Evaluation of deep learning techniques for deforestation detection in the Brazilian Amazon and cerrado biomes from remote sensing imagery", "title_link": "https://www.mdpi.com/663100", "publication_info": "M Ortega Adarme, R Queiroz Feitosa, P Nigri Happ\u2026\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "\u2026 to climate change and biodiversity reduction. Therefore, the \u2026 , the present work evaluates \nDeep Learning-based strategies \u2026 The strategies based on Deep Learning achieved the best \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3562953489532069401&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:GSbMRlIncjEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3562953489532069401&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] An Image is Worth a Thousand Species: Scaling high-resolution plant biodiversity prediction to biome-level using citizen science data and remote sensing\u00a0\u2026", "title_link": "https://biss.pensoft.net/article/74052/download/pdf/", "publication_info": "L Gillespie, M Ruffley\u2026\u00a0- Biodiversity Information\u00a0\u2026, 2021 - biss.pensoft.net", "snippet": "\u2026 can be used to build a plant biodiversity map across California with unparalleled accuracy. \n\u2026 , this deep learning-enabled method could be deployed to automatically map biodiversity at \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7722986253028186373&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:BVn4OBSPLWsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7722986253028186373&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Marine Animal Detection and Recognition with Advanced Deep Learning Models.", "title_link": "http://ceur-ws.org/Vol-1866/paper_166.pdf", "publication_info": "P Zhuang, L Xing, Y Liu, S Guo, Y Qiao\u00a0- CLEF (Working Notes), 2017 - ceur-ws.org", "snippet": "\u2026 Driven by the increasing demand of ecological surveillance and biodiversity monitoring \nunder the water, more sea-related multimedia data were collected with the aid of advanced \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14362195556527186600&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:qCJ_tcPEUMcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "An efficient approach based on privacy-preserving deep learning for satellite image classification", "title_link": "https://www.mdpi.com/2072-4292/13/11/2221", "publication_info": "M Alkhelaiwi, W Boulila, J Ahmad, A Koubaa, M Driss\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 biodiversity monitoring. Recent updates in the field have also introduced various deep learning \n(\u2026 that takes advantage of privacy-preserving deep learning (PPDL)-based techniques to \u2026", "cited_by": "https://scholar.google.com/scholar?cites=670722442941643602&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=2zqBGkYAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=670722442941643602&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[BOOK][B] Multimedia tools and applications for environmental & biodiversity informatics", "title_link": "https://link.springer.com/content/pdf/10.1007/978-3-319-76445-0.pdf", "publication_info": "A Joly, S Vrochidis, K Karatzas, A Karppinen, P Bonnet - 2018 - Springer", "snippet": "\u2026 They introduce several deep learning architectures that are \u2026 More precisely, it proposes \na deep learning approach to \u2026 the potential of the deep learning approach for this problem. It \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7261050993561433084&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=GM4IN0AAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=7261050993561433084&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning", "title_link": "https://www.pnas.org/doi/abs/10.1073/pnas.1719367115", "publication_info": "MS Norouzzadeh, A Nguyen\u2026\u00a0- Proceedings of the\u00a0\u2026, 2018 - National Acad Sciences", "snippet": "\u2026 and counting could improve all biology missions that require identifying species and counting \nindividuals, including animal monitoring and management, examining biodiversity, and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5857204489400607613&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:feOLR3P4SFEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5857204489400607613&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A comprehensive comparison on current deep learning approaches for plant image classification", "title_link": "https://iopscience.iop.org/article/10.1088/1742-6596/1873/1/012002/meta", "publication_info": "CL Zhou, LM Ge, YB Guo, DM Zhou\u2026\u00a0- Journal of Physics\u00a0\u2026, 2021 - iopscience.iop.org", "snippet": "\u2026 in understanding, protecting and conserving biodiversity. Traditional plant taxonomy needs \n\u2026 years by deep learning (DL) methods. In this study, we first reviewed current deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17392211687029815205&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:pTfPp2GMXfEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17392211687029815205&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] A new mobile application of agricultural pests recognition using deep learning in cloud computing system", "title_link": "https://www.sciencedirect.com/science/article/pii/S1110016821001642", "publication_info": "ME Karar, F Alsunaydi, S Albusaymi\u2026\u00a0- Alexandria Engineering\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 for example, insect counting as a biodiversity index [8]. In agriculture, deep learning methods \nsuch as \u2026 This study showed that the performance of deep learning solution is better than the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14496749173599920363&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:62Bc-pDMLskJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14496749173599920363&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning\u2010based methods for individual recognition in small birds", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13436", "publication_info": "AC Ferreira, LR Silva, F Renna\u2026\u00a0- Methods in Ecology\u00a0\u2026, 2020 - Wiley Online Library", "snippet": "\u2026 Overall, our work demonstrates the feasibility of applying state-of-the-art deep learning tools \nfor individual identification of birds, both in the laboratory and in the wild. These techniques \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6346668448210720915&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:k5jH2lPlE1gJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6346668448210720915&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Cyber-Physical System for Environmental Monitoring Based on Deep Learning", "title_link": "https://www.mdpi.com/1424-8220/21/11/3655", "publication_info": "\u00cd Monedero, J Barbancho, R M\u00e1rquez, JF Beltr\u00e1n\u00a0- Sensors, 2021 - mdpi.com", "snippet": "\u2026 This paper proposes a deep learning classification sound system for execution over CPS. \u2026 \nbiological acoustic targets as well as analyzing biodiversity indices in the natural environment. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8613545955203680679&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=XVK_1K4AAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=8613545955203680679&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Snapshot Safari: A large-scale collaborative to monitor Africa's remarkable biodiversity", "title_link": "http://www.scielo.org.za/scielo.php?pid=S0038-23532021000100007&script=sci_arttext&tlng=es", "publication_info": "LE Pardo, S Bombaci, SE Huebner\u2026\u00a0- South African Journal\u00a0\u2026, 2021 - scielo.org.za", "snippet": "\u2026 The millions of images generated annually by the Serengeti grid have been utilised as \ntraining data for many deep learning algorithms developed to identify African mammal species \u2026", "cited_by": "https://scholar.google.com/scholar?cites=751378857042344314&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:enm_6RZvbQoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=751378857042344314&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] High throughput data acquisition and deep learning for insect ecoinformatics", "title_link": "https://www.frontiersin.org/articles/10.3389/fevo.2021.600931/full", "publication_info": "A Gerovichev, A Sadeh, V Winter\u2026\u00a0- Frontiers in Ecology\u00a0\u2026, 2021 - frontiersin.org", "snippet": "\u2026 How do agricultural intensification and urbanization impact insect biodiversity? \u2026 We describe \na software system, based on deep learning, to identify and characterize insects in images of \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1854733461111963098&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:2v2bjkFWvRkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1854733461111963098&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Dynamical assessment of aboveground and underground biodiversity with supportive AI", "title_link": "https://www.sciencedirect.com/science/article/pii/S2665917421001306", "publication_info": "M Funabashi, T Minami\u00a0- Measurement: Sensors, 2021 - Elsevier", "snippet": "\u2026 biodiversity assessment, we took a machine learning approach using deep learning neural \n\u2026 Using only seven parameters out of 74, the deep learning neural network succeeded in \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:1ZneNv5KWs8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "A deep learning model for fish classification base on DNA barcode", "title_link": "https://www.biorxiv.org/content/10.1101/2021.02.15.431244.abstract", "publication_info": "L Jin, J Yu, X Yuan, X Du\u00a0- bioRxiv, 2021 - biorxiv.org", "snippet": "\u2026 , fish taxonomy is an important part of biodiversity and is also the basis of fishery resources \n\u2026 identification and biodiversity studies. In this paper, a novel deep learning classification \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:3BOa9-VeELwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=13551435620552414172&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13551435620552414172&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Lifeclef bird identification task 2016: The arrival of deep learning", "title_link": "https://hal.archives-ouvertes.fr/hal-01373779/", "publication_info": "H Go\u00ebau, H Glotin, WP Vellinga\u2026\u00a0- \u2026\u00a0and Labs of the\u00a0\u2026, 2016 - hal.archives-ouvertes.fr", "snippet": "\u2026 development of humanity as well as for biodiversity conservation. The general public as \u2026 \ninitiatives related to ecological surveillance or biodiversity conservation. The LifeCLEF Bird \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16807533792624422427&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:G67AK-9aQOkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16807533792624422427&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "An Automatic Method for Tree Species Point Cloud Segmentation Based on Deep Learning", "title_link": "https://link.springer.com/article/10.1007/s12524-021-01358-x", "publication_info": "L Pu, J Xv, F Deng\u00a0- Journal of the Indian Society of Remote Sensing, 2021 - Springer", "snippet": "\u2026 management, and biodiversity research. Recently, \u2026 deep learning theory is effectively utilized \nto process 3D point clouds, such as extracting the features of data. However, deep learning\u2026", "cited_by": "https://scholar.google.com/scholar?cites=17678407382003404149&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:dc30htlRVvUJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17678407382003404149&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Efficiently deep learning for monitoring Ipomoea cairica (L.) sweets in the wild", "title_link": "http://www.aimspress.com/aimspress-data/mbe/2021/2/PDF/mbe-18-02-060.pdf", "publication_info": "F Tang, D Zhang, X Zhao\u00a0- Mathematical Biosciences and\u00a0\u2026, 2021 - aimspress.com", "snippet": "\u2026 Abstract: Ipomoea cairica (L.) sweets are an invasive weed which has caused serious harm \nto the biodiversity and stability of the ecosystem. It is very important to accurately and rapidly \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3731974402639950479&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:j3I0RPKiyjMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3731974402639950479&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Long-term deep learning-facilitated environmental acoustic monitoring in the Capital Region of New York State", "title_link": "https://www.sciencedirect.com/science/article/pii/S1574954121000339", "publication_info": "MM Morgan, J Braasch\u00a0- Ecological Informatics, 2021 - Elsevier", "snippet": "\u2026 a robust, minimally disruptive, long-term approach to monitoring species interactions, \nparticularly because many indicator species of environmental health factors such as biodiversity, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3670610057777862962&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:MlnTWmag8DIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3670610057777862962&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for all: managing and analyzing underwater and remote sensing imagery on the web using BisQue", "title_link": "https://escholarship.org/uc/item/9z73t7hv", "publication_info": "D Fedorov, K Kvilekval, B Doheny, S Sampson, R Miller\u2026 - 2017 - escholarship.org", "snippet": "\u2026 are inherent in marine science, including biodiversity observation. Imagery is a promising \u2026 \nWe are developing a deep learning service for automated image classification. The service \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7827457856078130795&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:a67gzXK3oGwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[HTML][HTML] Application of deep learning in aquatic bioassessment: Towards automated identification of non-biting midges", "title_link": "https://www.sciencedirect.com/science/article/pii/S0048969719351526", "publication_info": "D Milo\u0161evi\u0107, A Milosavljevi\u0107, B Predi\u0107\u2026\u00a0- Science of the Total\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 A cost-effective approach that allows for reliable information regarding aquatic biodiversity \nis essential for the successful implementation of monitoring programs world-wide. The \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6256311351410559403&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:qwkS2Qbi0lYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6256311351410559403&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] AI naturalists might hold the key to unlocking biodiversity data in social media imagery", "title_link": "https://www.sciencedirect.com/science/article/pii/S2666389920301574", "publication_info": "TA August, OL Pescott, A Joly, P Bonnet\u00a0- Patterns, 2020 - Elsevier", "snippet": "\u2026 Automated identification has made considerable progress thanks to the development of deep \nlearning and convolutional neural networks (CNNs) in particular. For example, Go\u00ebau and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11684717687625109879&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=HTF5OegAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=11684717687625109879&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Insect biodiversity in agriculture using IoT: opportunities and needs for further research", "title_link": "https://ieeexplore.ieee.org/abstract/document/9682153/", "publication_info": "JL Zapico, F Ahlgren, M Zennaro\u00a0- 2021 IEEE Globecom\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 [17] TT H\u00f8ye et al., \u201cDeep learning and computer vision will transform entomology,\u201d Proc \u2026 \nDeep learning approaches for challenging species and gender identification of mosquito vectors\u2026", "cited_by": "https://scholar.google.com/scholar?cites=10325206837701637444&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:RPWj4emASo8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10325206837701637444&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Rapid prototyping of species classifiers using deep learning: A guide for non-experts", "title_link": "https://www.authorea.com/doi/full/10.22541/au.158316446.65534248", "publication_info": "HN Chege\u00a0- Authorea Preprints, 2020 - authorea.com", "snippet": "\u2026 Deep learning algorithms are revolutionizing how hypothesis \u2026 its subfields, the use of deep \nlearning is slowly but steadily \u2026 Such tools have implications for citizen science, biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16922668503720551048&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:iGL0D1hl2eoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Regional mapping and spatial distribution analysis of canopy palms in an amazon forest using deep learning and VHR images", "title_link": "https://www.mdpi.com/766500", "publication_info": "FH Wagner, R Dalagnol, X Tagle Casapia, AS Streher\u2026\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "\u2026 Tropical ecosystems in this context are of primary importance as they host a large part of \nthe biodiversity, for example, sixteen of the 25 global biodiversity hotspots are located in the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2220250012588339871&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:n3LigJ_pzx4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2220250012588339871&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for detecting and classifying ocean objects: application of YoloV3 for iceberg\u2013ship discrimination", "title_link": "https://www.mdpi.com/930032", "publication_info": "FS Hass, J Jokar Arsanjani\u00a0- ISPRS International Journal of Geo\u00a0\u2026, 2020 - mdpi.com", "snippet": "\u2026 Hence, this study aims at proposing a deep learning model \u2026 is capable of training a deep \nlearning model with reliable \u2026 , shipping industries and biodiversity analysts. The main difficulties \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5860296768109058575&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:D5qChdz0U1EJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5860296768109058575&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Comparing deep learning and shallow learning for large-scale wetland classification in Alberta, Canada", "title_link": "https://www.mdpi.com/2072-4292/12/1/2", "publication_info": "ER DeLancey, JF Simms, M Mahdianpari, B Brisco\u2026\u00a0- Remote Sensing, 2019 - mdpi.com", "snippet": "\u2026 The use of deep learning in remote sensing is a more recent development and it is gaining \npopularity [14,15,16,17,18]. Of the many types of deep learning approaches that exist, we \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5363504823634552596&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:FOfUUzj_bkoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5363504823634552596&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Deep Learning for Forest Species Identification Based on Macroscopic Images", "title_link": "https://www.researchgate.net/profile/Juan-Valverde-2/publication/325299970_Deep_Learning_for_Forest_Species_Identification_Based_on_Macroscopic_Images/links/5b04539f4585154aeb07f0de/Deep-Learning-for-Forest-Species-Identification-Based-on-Macroscopic-Images.pdf", "publication_info": "E Mata-Montero, D Arias-Aguilar\u2026\u00a0- Biodiversity\u00a0\u2026, 2018 - researchgate.net", "snippet": "\u2026 years, deep learning \u2026 deep learning techniques extract and learn by themselves the relevant \nfeatures from large datasets. One of the main limitations for the application of deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16602676784385705763&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:I0fvFZKOaOYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16602676784385705763&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Remote sensing and deep learning for environmental policy support: from theory to practice", "title_link": "https://ieeexplore.ieee.org/abstract/document/9554514/", "publication_info": "S Heremans, F Turkelboom, M Verhulst\u2026\u00a0- \u2026\u00a0and Remote Sensing\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 Data-driven environmental governance is gaining importance for tackling the current \nbiodiversity and climate crises. Remote sensing can provide an efficient alternative to expensive \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:dF1HtS7GwroJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=13457536540448611700&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13457536540448611700&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Assessing the potential for deep learning and computer vision to identify bumble bee species from images", "title_link": "https://www.nature.com/articles/s41598-021-87210-1", "publication_info": "BJ Spiesman, C Gratton, RG Hatfield, WH Hsu\u2026\u00a0- Scientific reports, 2021 - nature.com", "snippet": "\u2026 With mounting evidence of a global decline in insect biodiversity 41,42 , we need these AI-\u2026 \ninsect biodiversity trends compared to trends in relatively simple measures of biomass eg, 46 . \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7248893507031496046&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=JQoJRcIAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=7248893507031496046&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "DEPP: deep learning enables extending species trees using single genes", "title_link": "https://www.biorxiv.org/content/10.1101/2021.01.22.427808.abstract", "publication_info": "Y Jiang, M Balaban, Q Zhu, S Mirarab\u00a0- bioRxiv, 2021 - biorxiv.org", "snippet": "\u2026 Identifying samples in an evolutionary context is a fundamental step in the study of microbiome, \nand more broadly, biodiversity. Extending a reference phylogeny by placing new query \u2026", "cited_by": "https://scholar.google.com/scholar?cites=564772709036948454&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=uxSj18QAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=564772709036948454&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Detection of invasive vegetation through UAV and Deep Learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/9605371/", "publication_info": "CP Charles, PHC Kim, AG de Almeida\u2026\u00a0- 2021 Latin American\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 can cause irreversible adverse impacts on biodiversity and affect economic productivity in \n\u2026 Therefore, this paper proposes the classification of images using Deep Learning algorithms \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:quQeTB_7WDYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=3916155987838297258&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3916155987838297258&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for underwater noise classification", "title_link": "https://asa.scitation.org/doi/abs/10.1121/1.5101972", "publication_info": "JL Chen, S Nguyen, JM Trader, A Moore\u2026\u00a0- The Journal of the\u00a0\u2026, 2019 - asa.scitation.org", "snippet": "\u2026 Deep-learning models have surpassed many computer-vision benchmarks and groups \u2026 \nnoise on sea life and monitoring the health and biodiversity of the ocean. In this work, we present \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16432671881024323436&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:bD8BAwOUDOQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16432671881024323436&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Reducing Manual Supervision Required for Biodiversity Monitoring with Self-Supervised Learning", "title_link": "https://biss.pensoft.net/article/74047/download/pdf/", "publication_info": "O Pantazis, G Brostow, K Jones\u2026\u00a0- Biodiversity Information\u00a0\u2026, 2021 - biss.pensoft.net", "snippet": "Recent years have ushered in a vast array of different types of low cost and reliable sensors \nthat are capable of capturing large quantities of audio and visual information from the \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:CHCkbWlI6rEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=12820138906911797256&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12820138906911797256&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Performance Analysis of Biomass Energy using Machine and Deep Learning Approaches", "title_link": "https://iopscience.iop.org/article/10.1088/1742-6596/2089/1/012003/meta", "publication_info": "S Sharma, P Khanra\u2026\u00a0- Journal of Physics\u00a0\u2026, 2021 - iopscience.iop.org", "snippet": "\u2026 hampering the biodiversity. Therefore, in this study Machine and Deep Learning algorithms \nare \u2026 Moreover, this work introduces number of Machine and Deep Learning approaches to \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:LR8aYxhY5fMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=17574549982648344365&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17574549982648344365&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Scaling vegetation dynamics: a metamodeling approach based on deep learning", "title_link": "https://scholarsarchive.byu.edu/iemssconference/2018/Stream-A/35/", "publication_info": "W Rammer, R Seidl - 2018 - scholarsarchive.byu.edu", "snippet": "\u2026 To tackle global issues such as climate change or biodiversity \u2026 Deep Learning is an emerging \nbranch of machine learning, \u2026 , total ecosystem carbon or biodiversity) are derived from PBM \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comhttps://scholar.googleusercontent.com/scholar?q=cache:SMjBJBxK5VcJ:scholar.google.com/+biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Learning from the deep with deep learning", "title_link": "https://proceedings.spp-online.org/article/view/799", "publication_info": "P Naval\u00a0- Proceedings of the Samahang Pisika ng\u00a0\u2026, 2018 - proceedings.spp-online.org", "snippet": "\u2026 , fish population density, and biomass estimation from underwater video sequences, and \npresent an integrated semi-automated fish visual census system for fish biodiversity monitoring \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=11874924109351925869&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=11874924109351925869&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Assessment of Landsat Based Deep-Learning Membership Analysis for Development of from\u2013to Change Time Series in the Prairie Region of Canada from 1984 to\u00a0\u2026", "title_link": "https://www.mdpi.com/993828", "publication_info": "D Pouliot, N Alavi, S Wilson, J Duffe, J Pasher\u2026\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 on wildlife populations and biodiversity, ultimately leading to \u2026 It employed a deep-learning \nconvolutional neural network to \u2026 Results showed that the deep-learning method produced the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8725951295748674716&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:nJR1rnjOGHkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8725951295748674716&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Application of Deep Learning to Automated Species Identification Systems", "title_link": "https://search.proquest.com/openview/fa32e9b3484e6c98db8f80382579aed7/1?pq-origsite=gscholar&cbl=18750&diss=y", "publication_info": "A Khalighifar - 2020 - search.proquest.com", "snippet": "\u2026 these tools by challenging an advanced deep-learning technique, TensorFlow Inception \nv3, \u2026 of global biodiversity. Here, I present an exploration of one advanced, deep-learning-based \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:2BKTNb7D2mIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[HTML][HTML] Deep convolutional neural networks to monitor coralligenous reefs: operationalizing biodiversity and ecological assessment", "title_link": "https://www.sciencedirect.com/science/article/pii/S1574954120300601", "publication_info": "G Marre, CDA Braga, D Ienco, S Luque, F Holon\u2026\u00a0- Ecological\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 We trained LR models with different inputs, from the features learned by the deep learning \nmodel (output of the concatenation layer feeding the MLP; see Figure 6Error! Reference \u2026", "cited_by": "https://scholar.google.com/scholar?cites=546730184880280563&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:89PF2TRglgcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=546730184880280563&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automatic detection of endangered species in video and satellite images using deep learning", "title_link": "https://upcommons.upc.edu/handle/2117/354384", "publication_info": "R Mart\u00edn Pinardel - 2020 - upcommons.upc.edu", "snippet": "\u2026 to work on processing techniques using Deep Learning (Convolutional Neural networks, \u2026 \nspecies and to give an adequate and rapid response to face the current biodiversity crisis. \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=14524929723901338959&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=14524929723901338959&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automated Visual Large Scale Monitoring of Faunal Biodiversity", "title_link": "https://link.springer.com/article/10.1134/S1054661821030214", "publication_info": "B Radig, P Bodesheim, D Korsch, J Denzler\u2026\u00a0- Pattern Recognition and\u00a0\u2026, 2021 - Springer", "snippet": "\u2026 To make use of the additional depth information, we extend the Mask R-CNN [15] deep \nlearning instance segmentation architecture to D-Mask R-CNN [14]. In Mask R-CNN, color image \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10276097662912390870&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=bhpi3vgAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=10276097662912390870&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] State of the Art in Computational Bioacoustics and Machine Learning: How far have we come?", "title_link": "https://biss.pensoft.net/article/37227/download/pdf/", "publication_info": "D Stowell\u00a0- Biodiversity Information Science and Standards, 2019 - biss.pensoft.net", "snippet": "\u2026 need to understand about deep learning? This contribution will \u2026 We will discuss which type \nof deep learning networks are \u2026 issues in integrating deep learning predictions with existing \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17217566140466800173&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:LSZRoy4V8e4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17217566140466800173&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Fish recognition in underwater environments using deep learning and audio data", "title_link": "https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11752/117520G/Fish-recognition-in-underwater-environments-using-deep-learning-and-audio/10.1117/12.2585991.short", "publication_info": "JF Laplante, MA Akhloufi\u2026\u00a0- Ocean Sensing and\u00a0\u2026, 2021 - spiedigitallibrary.org", "snippet": "\u2026 of marine biodiversity. As \u2026 biodiversity and that this index presents a better resolution than \nvisual identification by divers for the purpose of evaluating the effects on marine biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:zIN7mKWXu3AJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=8123253090376451020&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8123253090376451020&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "The Role of Citizen Science and Deep Learning in Camera Trapping", "title_link": "https://www.mdpi.com/1271856", "publication_info": "M Adam, P Tom\u00e1\u0161ek, J Lehej\u010dek, J Trojan, T J\u016fnek\u00a0- Sustainability, 2021 - mdpi.com", "snippet": "\u2026 However, since every research project is done under different environmental conditions (geographical, \nbiodiversity region, weather conditions, image background, etc.), the proposed \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9893348541968065543&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:B6Qi6xQ8TIkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9893348541968065543&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Modelling the niches of wild and domesticated Ungulate species using deep learning", "title_link": "https://www.biorxiv.org/content/10.1101/744441.abstract", "publication_info": "M Rademaker, L Hogeweg, R Vos\u00a0- BioRxiv, 2019 - biorxiv.org", "snippet": "\u2026 Knowledge of global biodiversity remains limited by geographic and taxonomic sampling \u2026 \nHowever, the past two decades have seen a strong increase in the use of Deep Learning (DL) \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2986605353762039855&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:LyhE276NcikJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2986605353762039855&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A novel model integrating deep learning for land use/cover change reconstruction: A case study of zhenlai county, northeast china", "title_link": "https://www.mdpi.com/852990", "publication_info": "Z Yubo, Y Zhuoran, Y Jiuchun, Y Yuanyuan\u2026\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "\u2026 LUCC not only accelerates global warming but also causes widespread and irreversible \nloss of biodiversity. Therefore, LUCC reconstruction has important scientific and practical value \u2026", "cited_by": "https://scholar.google.com/scholar?cites=12006949410162956247&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:11fZfN9AoaYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12006949410162956247&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Forest species classification of uav hyperspectral image using deep learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/9327690/", "publication_info": "J Liang, P Li, H Zhao, L Han\u2026\u00a0- 2020 Chinese Automation\u00a0\u2026, 2020 - ieeexplore.ieee.org", "snippet": "Forest species classification is essential for surveying of forest resource, biodiversity \nresearch, and community structure. The tree species level classification can be achieved by \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14908311169837230486&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:lukidwX25M4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Plant Species Identification from Leaf Images Using Deep Learning Models (CNN-LSTM Architecture)", "title_link": "https://www.ajol.info/index.php/tjfnc/article/view/217008", "publication_info": "J Banzi, T Abayo\u00a0- Tanzania Journal of Forestry and Nature Conservation, 2021 - ajol.info", "snippet": "\u2026 Species knowledge is important for biodiversity conservation. Identification of plants by \u2026 \nsimple leaves images of plants, through deep learning methodologies. Training of the models \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:_jdoe5yCGCsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "An Adaptive Automatic Approach to Filtering Empty Images from Camera Traps Using a Deep Learning Model", "title_link": "https://wildlife.onlinelibrary.wiley.com/doi/abs/10.1002/wsb.1176", "publication_info": "DQ Yang, GP Ren, K Tan, ZP Huang\u2026\u00a0- Wildlife Society\u00a0\u2026, 2021 - Wiley Online Library", "snippet": "\u2026 Deep learning is a machine learning method that provides a \u2026 training images for training \ndeep learning models is labor \u2026 Our study explores an adaptive deep learning method to use \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14919933620607102555&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:W66xKJRADs8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[PDF][PDF] A Portuguese Flora Identification Tool Using Deep Learning", "title_link": "https://repositorio-aberto.up.pt/bitstream/10216/130189/2/429763.pdf", "publication_info": "M\u00c2R Marques - 2020 - repositorio-aberto.up.pt", "snippet": "\u2026 are part of the biodiversity that fills this world with unique places and landscapes. Biodiversity \ncan be \u2026 We started by gathering information regarding the use of deep learning for image \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:UCrMZJ0dEtoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Detection of insect health with deep learning on near-infrared sensor data", "title_link": "https://www.biorxiv.org/content/10.1101/2021.11.15.468635.abstract", "publication_info": "E Bick, S Edwards, H Henrik\u00a0- bioRxiv, 2021 - biorxiv.org", "snippet": "\u2026 Here we show that deep learning in trained convolutional neural networks in conjunction \u2026 \nbiodiversity and the rapid assessment of disease carrying individuals in vector populations. \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:UQySlqrWldQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=15318385735729548369&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15318385735729548369&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A deep learning algorithm for automatic identification of coral reef fish species on images", "title_link": "https://hal.archives-ouvertes.fr/lirmm-01883997/", "publication_info": "S Villon, D Mouillot, M Chaumont\u2026\u00a0- \u2026\u00a0Marine Biodiversity, 2018 - hal.archives-ouvertes.fr", "snippet": "One of the current challenges of marine ecology is to monitor biodiversity accurately and \nefficiently at large spatial scale and at high frequency. Therefore, underwater surveys based on \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=2624836110121621968&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=2624836110121621968&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Cyber-physical system for environmental monitoring based on deep learning", "title_link": "https://idus.us.es/handle/11441/111399", "publication_info": "IL Monedero Goicoechea\u2026\u00a0- Sensors, 21 (11)\u00a0\u2026, 2021 - idus.us.es", "snippet": "\u2026 This paper proposes a deep learning classification sound system for execution over CPS. \u2026 \nbiological acoustic targets as well as analyzing biodiversity indices in the natural environment. \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:HJ6SOOXYDNIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[HTML][HTML] Automatic underwater fish species classification with limited data using few-shot learning", "title_link": "https://www.sciencedirect.com/science/article/pii/S1574954121001114", "publication_info": "S Villon, C Iovan, M Mangeas, T Claverie, D Mouillot\u2026\u00a0- Ecological\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 used to monitor marine biodiversity, and the \u2026 deep-learning methods to identify coral reef \nfish species on images. More specifically, we aim to determine how well a classic deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8333483487732642243&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=MPSC3VgAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=8333483487732642243&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Marine Data Prediction: An Evaluation of Machine Learning, Deep Learning, and Statistical Predictive Models", "title_link": "https://search.proquest.com/openview/6d2db77ab33f58450988f1d269a26daf/1?pq-origsite=gscholar&cbl=237303", "publication_info": "A Ahmed, A Fathalla, S Ahmad\u2026\u00a0- Computational\u00a0\u2026, 2021 - search.proquest.com", "snippet": "\u2026 data such as sea surface temperature (SST) and Significant Wave Height (SWH) is a vital \ntask in a variety of disciplines, including marine activities, deep-sea, and marine biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:JSMB_xyLMWAJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Ensemble Deep Learning Models for Fine-grained Plant Species Identification", "title_link": "https://ieeexplore.ieee.org/abstract/document/9718387/", "publication_info": "OA Malik, M Faisal, BR Hussein\u00a0- 2021 IEEE Asia-Pacific\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 Plant species identification has an important role in the preservation of biodiversity as \nwell as the discovery of new species. The manual process of plant species identification is \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:4CFIS4Ha6qoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=12315896379846697440&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12315896379846697440&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Deep learning for weed identification based on seed images", "title_link": "https://biss.pensoft.net/article/25749/download/pdf/", "publication_info": "F Pando, I Heredia, C Aedo, M Velayos Rodr\u00edguez\u2026 - 2018 - biss.pensoft.net", "snippet": "Reliable plant species identification from seeds is intrinsically difficult due to the scarcity of \nfeatures and because it requires specialized expertise that is becoming increasingly rarer, as \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14004972763835922432&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:APh19YaoW8IJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14004972763835922432&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] CLASSIFICATION OF AERIAL CACTUS FOR CONSERVING BIODIVERSITY HOTSPOT ZONES USING DEEP CONVOLUTIONAL NEURAL NETWORK VGG16", "title_link": "http://103.47.12.35/bitstream/handle/1/1773/1613101843_VISHAL%20YADAV_FinalProjectReport%20-%20Vishal%20Yadav.pdf?sequence=1&isAllowed=y", "publication_info": "V YADAV - 2021 - 103.47.12.35", "snippet": "\u2026 So our aim is to identify this biodiversity ecosystem by using automated surveillance and \u2026 \ndeep learning based identification of cactus and other biodiversity vegetables latest works. \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:tgHU1a6vmx8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=2277607202012529078&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2277607202012529078&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning algorithms improve automated identification of Chagas disease vectors", "title_link": "https://academic.oup.com/jme/article-abstract/56/5/1404/5498005", "publication_info": "A Khalighifar, E Komp, JM Ramsey\u2026\u00a0- Journal of medical\u00a0\u2026, 2019 - academic.oup.com", "snippet": "\u2026 The purpose of this study was to test whether deep learning techniques can improve abilities \n\u2026 identification capabilities in medical entomology, and more broadly in biodiversity science. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17463825076801926363&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:23RWSmH4W_IJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17463825076801926363&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Classical Machine Learning and Deep Learning Approaches for Global 10m Land Cover", "title_link": "https://ui.adsabs.harvard.edu/abs/2021AGUFMGC43D..03B/abstract", "publication_info": "T Birch, F Stolle, R Van De Kerchove\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2021 - ui.adsabs.harvard.edu", "snippet": "\u2026 observation data, alongside Dynamic World, a deep learning neural net approach to a near \nreal-\u2026 of areas including biodiversity, food security, carbon assessment and climate modeling. \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Label-free imaging flow cytometry for phenotypic analysis of microalgae populations using deep learning", "title_link": "https://opg.optica.org/abstract.cfm?uri=FiO-2021-FM3D.4", "publication_info": "\u00c7 I\u015f\u0131l, K de Haan, Z G\u04e7r\u04e7cs, HC Koydemir\u2026\u00a0- Frontiers in\u00a0\u2026, 2021 - opg.optica.org", "snippet": "\u2026 about the long-term effects of pollution on biodiversity in the marine environment [1]. \u2026 \nThe second method is a deep learning-based classification algorithm that identifies different \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:rEZGHA8SPq4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Forestnet: Classifying drivers of deforestation in indonesia using deep learning on satellite imagery", "title_link": "https://arxiv.org/abs/2011.05479", "publication_info": "J Irvin, H Sheng, N Ramachandran\u2026\u00a0- arXiv preprint arXiv\u00a0\u2026, 2020 - arxiv.org", "snippet": "\u2026 The preservation of forests is crucial for preventing loss of biodiversity, managing air and \u2026 \nimagery coupled with advancements in deep learning methods present opportunities to \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16153228571326831856&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:8FygWc3LK-AJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16153228571326831856&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "AUTOMATIC FISH DETECTION FROM DIFFERENT MARINE ENVIRONMENTS VIDEO USING DEEP LEARNING.", "title_link": "https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=16821750&AN=156194412&h=33DDAAJoNAqD6eEOu6QJlocgNeWDeQ5e%2B8xJtQiwQLVTgbahfWh9NJ6Wl3hwbSAvDUU8ypCD8dh%2Fjq1QDqyM3w%3D%3D&crl=c", "publication_info": "A Loulidi, R Houssa, L Buhl-Mortensen\u2026\u00a0- \u2026\u00a0Archives of the\u00a0\u2026, 2021 - search.ebscohost.com", "snippet": "\u2026 The marine environment provides many ecosystems that support habitats biodiversity. \u2026 \nThe current study evaluates the possibility of using deep learning methods in particular the \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=1302199903111725904&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=1302199903111725904&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] THE EFFECT OF BACKGROUND ON ADeep LEARNING MODEL IN IDENTIFYING IMAGES OF BUTTERFLY SPECIES", "title_link": "https://www.academia.edu/download/58604625/8119elelij01.pdf", "publication_info": "T Xi, J Wang, Y Han, T Wang, L Ji - academia.edu", "snippet": "\u2026 The biodiversity of Lepidoptera plays an vital role in \u2026 In this paper, we propose a deep \nlearning method with improved \u2026 amount of data to train deep learning models, which could have \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:NGArpr-hVLsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=13498591827634905140&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13498591827634905140&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Wildlife Insights: A platform to understand and share biodiversity information from in-situ passive sensors", "title_link": "https://ui.adsabs.harvard.edu/abs/2020AGUFMB071...09A/abstract", "publication_info": "JA Ahumada, T Birch\u00a0- AGU Fall Meeting Abstracts, 2020 - ui.adsabs.harvard.edu", "snippet": "\u2026 Without these tools, biodiversity managers and other \u2026 , including novel integration of deep \nlearning models for species \u2026 risks of publishing shared biodiversity data and a framework to \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=14905570976008386892&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=14905570976008386892&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Implementation of Stacked Autoencoder with RBM for Predicting and Monitoring Aquatic Biodiversity", "title_link": "https://www.researchgate.net/profile/Murugan-Venkatachalam-3/publication/342360755_Implementation_of_Stacked_Autoencoder_with_RBM_for_Predicting_and_Monitoring_Aquatic_Biodiversity/links/6197d4af61f0987720b4c380/Implementation-of-Stacked-Autoencoder-with-RBM-for-Predicting-and-Monitoring-Aquatic-Biodiversity.pdf", "publication_info": "V Murugan, JJ Emilyn, M Prabu - researchgate.net", "snippet": "\u2026 Aquatic biodiversity depends on water quality parameters for survival. Our research focuses \n\u2026 the management of aquatic biodiversity and water quality. Deep learning with its unique self\u2026", "cited_by": "https://scholar.google.com/scholar?q=related:Z1xUDW2yfPcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "AI recognition of infrared camera image of wild animals based on deep learning: Northeast Tiger and Leopard National Park for example", "title_link": "http://www.mammal.cn/EN/abstract/abstract3330.shtml", "publication_info": "G Yinan, TAN Mengyu, W Zhen, Z Guojing\u2026\u00a0- Acta Theriologica\u00a0\u2026, 2019 - mammal.cn", "snippet": "\u2026 to meet the demand of fast automatic identification, this study, using Northeast Tiger and \nLeopard National Park as an example, is to explore the practicability of using deep learning, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9296751365161337216&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:gMGRPRyyBIEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9296751365161337216&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Detection of Seashore Debris with Fixed Camera Images using Computer Vision and Deep learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/9651572/", "publication_info": "A Kankane, D Kang\u00a0- 2021 6th International Conference on\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 Abstract\u2014Marine debris is impacting coastal landscapes majorly by affecting biodiversity, \nimpairing recreational uses, causing losses to fishing industries, maritime industries, etc. In \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:dWPLt3YIqE0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Automatic detection of endangered species in video and satellite images using deep learning", "title_link": "https://upcommons.upc.edu/handle/2117/347191", "publication_info": "D Torres Cirina - 2021 - upcommons.upc.edu", "snippet": "\u2026 A work on processing techniques using Deep Learning (Convolutional Neural Networks) to \n\u2026 adequate and rapid response to face the current biodiversity crisis. For this project there isn\u2019t \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comhttps://scholar.googleusercontent.com/scholar?q=cache:d3tGaMe1eUMJ:scholar.google.com/+biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[HTML][HTML] How deep learning extracts and learns leaf features for plant classification", "title_link": "https://www.sciencedirect.com/science/article/pii/S003132031730198X", "publication_info": "SH Lee, CS Chan, SJ Mayo, P Remagnino\u00a0- Pattern Recognition, 2017 - Elsevier", "snippet": "\u2026 Our paper begins with an introduction to deep learning. Next, we \u2026 Then, we introduce the \nidea of deep learning for automatic \u2026 High resolution satellite imagery for tropical biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17838286771324908958&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=P5OQ_9EAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=17838286771324908958&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "An OCR Post-Correction Approach Using Deep Learning for Processing Medical Reports", "title_link": "https://ieeexplore.ieee.org/abstract/document/9448197/", "publication_info": "S Karthikeyan, AGS de Herrera\u2026\u00a0- IEEE Transactions on\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 Recent advancements in the field of Machine learning and deep learning has provided \u2026 \nmodel, it is also evaluated on the publicly available Mining Biodiversity (MiBio) dataset [37]. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4528141313479756857&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:OUy7kogw1z4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4528141313479756857&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Application of deep learning in ecological resource research: Theories, methods, and challenges", "title_link": "https://link.springer.com/article/10.1007/s11430-019-9584-9", "publication_info": "Q Guo, S Jin, M Li, Q Yang, K Xu, Y Ju, J Zhang\u2026\u00a0- Science China Earth\u00a0\u2026, 2020 - Springer", "snippet": "\u2026 of deep learning in the field of ecological resource research, here, we first introduce the \nrelationship between deep learning \u2026 Second, applications of deep learning in classification and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13301315720097715951&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:71a-jSzEl7gJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13301315720097715951&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Detection of mulberry ripeness stages using deep learning models", "title_link": "https://ieeexplore.ieee.org/abstract/document/9481231/", "publication_info": "SHM Ashtiani, S Javanmardi, M Jahanbanifard\u2026\u00a0- IEEE\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 He is currently working as a Guest Researcher at the Naturalis Biodiversity Center, Leiden. \nHis research interests include artificial intelligence, machine learning, computer vision, and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7422954167309968342&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:1iOElnyhA2cJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7422954167309968342&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep-learning based high-resolution mapping shows woody vegetation densification in greater Maasai Mara ecosystem", "title_link": "https://www.sciencedirect.com/science/article/pii/S0034425720303230", "publication_info": "W Li, R Buitenwerf, M Munk, PK B\u00f8cher\u2026\u00a0- Remote Sensing of\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 They are globally important ecosystems for biodiversity and the livelihoods of millions of \npeople. Despite their importance, savannas are under large pressures due to increasing \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10546293011597647161&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=p-hJnQsAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=10546293011597647161&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Predicting the Dynamics of Forest Fire Spread from Satellite Imaging Using Deep Learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/9155734/", "publication_info": "R Jindal, AK Kunwar, A Kaur\u2026\u00a0- \u2026\u00a0on Electronics and\u00a0\u2026, 2020 - ieeexplore.ieee.org", "snippet": "\u2026 These fires present a challenge to the invaluable forest resources and the natural ecosystem \nof plants and animals, gravely upsetting the biodiversity and ecology of a region. Wildfires \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:XlJm67bWlYUJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Fish species classification in unconstrained underwater environments based on deep learning", "title_link": "https://aslopubs.onlinelibrary.wiley.com/doi/abs/10.1002/lom3.10113", "publication_info": "A Salman, A Jalal, F Shafait, A Mian\u2026\u00a0- Limnology and\u00a0\u2026, 2016 - Wiley Online Library", "snippet": "\u2026 The videos span a time period of 5 yr of monitoring the marine ecosystem of Taiwan coral \nreefs, one of the largest fish biodiversity environments in the world with more than 3000 \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2070474350204300526&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=X589yaIAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=2070474350204300526&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Diverse ocean noise classification using deep learning", "title_link": "https://www.sciencedirect.com/science/article/pii/S0003682X21002358", "publication_info": "B Mishachandar, S Vairamuthu\u00a0- Applied Acoustics, 2021 - Elsevier", "snippet": "\u2026 CNN is an extensively preferred choice of a deep learning model to perform acoustic tasks \nlike \u2026 This paper aims to cover a deep learning- based automatic ocean noise classification \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11641111117910868863&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:f4PtbeKIjaEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11641111117910868863&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep learning for image-based cassava disease detection", "title_link": "https://www.frontiersin.org/articles/10.3389/fpls.2017.01852/full", "publication_info": "A Ramcharan, K Baranowski, P McCloskey\u2026\u00a0- Frontiers in plant\u00a0\u2026, 2017 - frontiersin.org", "snippet": "\u2026 classes, offers a shortcut to training deep learning models because of lower computational \nrequirements\u2026 Here we investigated the potential for adapting an already trained deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17063191635939992295&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:56KeYmOizOwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17063191635939992295&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Crop mapping from image time series: Deep learning with multi-scale label hierarchies", "title_link": "https://www.sciencedirect.com/science/article/pii/S0034425721003230", "publication_info": "MO Turkoglu, S D'Aronco, G Perich, F Liebisch\u2026\u00a0- Remote Sensing of\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 In this work, we propose a deep learning network architecture for crop mapping that is \nhierarchical, to exploit a tree-structured label hierarchy built by domain experts; convolutional to \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4216173255914707681&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:4VpM7jzbgjoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4216173255914707681&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Counting trees at the city scale via merging multiple remote sensing platforms and deep learning", "title_link": "https://ui.adsabs.harvard.edu/abs/2021AGUFMSY15F..06K/abstract", "publication_info": "R Kwon, Y Ryu, S Zaheer\u00a0- AGU Fall Meeting Abstracts, 2021 - ui.adsabs.harvard.edu", "snippet": "\u2026 in increasing urban biodiversity, \u2026 -art deep learning based approaches have shown remarkable \nperformance for these tasks. Here we present a new method using various deep learning \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "An automated decadal survey of saguaro population using deep learning", "title_link": "https://ui.adsabs.harvard.edu/abs/2021AGUFM.B25E1496S/abstract", "publication_info": "X Shen, G Liang, X Feng\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2021 - ui.adsabs.harvard.edu", "snippet": "\u2026 Deep learning (DL) offers a unique opportunity to mapping plant population density in arid \n\u2026 Such mapping can provide unprecedented data for ecological and biodiversity studies. \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=3248940035900936257&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=3248940035900936257&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Exploring the potential of deep learning for classifying camera trap data of wildlife: a case study from Nepal", "title_link": "https://ui.adsabs.harvard.edu/abs/2021AGUFMGC45I0923M/abstract", "publication_info": "M Matin, T Shrestha, V Chitale\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2021 - ui.adsabs.harvard.edu", "snippet": "\u2026 Hindu Kush Himalaya (HKH) region accommodates four global biodiversity hotspots and it is \n\u2026 In our study, we explore three different approaches of deep learning methods to detect and \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "MRFusion: A Deep Learning architecture to fuse PAN and MS imagery for land cover mapping", "title_link": "https://arxiv.org/abs/1806.11452", "publication_info": "R Gaetano, D Ienco, K Ose, R Cresson\u00a0- arXiv preprint arXiv:1806.11452, 2018 - arxiv.org", "snippet": "\u2026 as assessing ecosystem status, monitoring biodiversity and providing inputs to conceive \u2026 \nHere, we propose a new deep learning architecture to jointly use PAN and MS imagery for a \u2026", "cited_by": "https://scholar.google.com/scholar?cites=461011863240333930&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:alqu2djXZQYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=461011863240333930&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Tutorial: Machine and Deep Learning for Earth Observation: Advanced Approaches and Practical Use Cases\u2013Abstract", "title_link": "https://agritrop.cirad.fr/600096", "publication_info": "D Ienco, R Interdonato - 2021 - agritrop.cirad.fr", "snippet": "\u2026 In this context, data-intensive methodologies such as machine and deep learning \u2026 open \nquestions remain unsolved (eg, biodiversity monitoring, urban mapping, deforestation tracking \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=11073922458238614999&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=11073922458238614999&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "LifeCLEF 2021 Teaser: Biodiversity Identification and Prediction Challenges", "title_link": "https://link.springer.com/chapter/10.1007/978-3-030-72240-1_70", "publication_info": "A Joly, H Go\u00ebau, E Cole, S Kahl, L Picek\u2026\u00a0- \u2026\u00a0on Information Retrieval, 2021 - Springer", "snippet": "\u2026 for this competition and point counts to assess biodiversity from this particular location in South \n\u2026 In the past few years, deep learning approaches have transformed the field of automated \u2026", "cited_by": "https://scholar.google.com/scholar?cites=278755134392334917&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=o2blBQQAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=278755134392334917&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Detecting Floating Marine Debris from Commercial Small Satellite Imagery with Deep Learning", "title_link": "https://ui.adsabs.harvard.edu/abs/2021AGUFMIN23A..04T/abstract", "publication_info": "L Thomas, A Shah\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2021 - ui.adsabs.harvard.edu", "snippet": "\u2026 leads to the loss of biodiversity. Large swaths of \u2026 deep learning, can be used to detect \nfloating marine debris in satellite imagery. This project presents an application of a deep learning \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[PDF][PDF] Deep Learning: The Great Challenge to Innovate: Highlighting Colombia's Food Industry", "title_link": "https://www.researchgate.net/profile/Gulfarida-Tulemisova/publication/358425625_ICICKM-Proceedings-Bangkok/links/620229022f2cd844ad7a4ccb/ICICKM-Proceedings-Bangkok.pdf#page=446", "publication_info": "BEM Pati\u00f1o\u00a0- International Conference on Intellectual Capital and\u00a0\u2026, 2015 - researchgate.net", "snippet": "\u2026 , a deep learning cycle \u2026 deep learning cycle will be relevant to each economic sector. In \nparticular, the food and beverage industry of Colombia depends largely on the rich biodiversity of \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7874067964565497081&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:-aQ1XRhPRm0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7874067964565497081&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for plant species classification using leaf vein morphometric", "title_link": "https://ieeexplore.ieee.org/abstract/document/8388220/", "publication_info": "J Wei Tan, SW Chang, S Abdul-Kareem\u2026\u00a0- \u2026\u00a0ACM transactions on\u00a0\u2026, 2018 - ieeexplore.ieee.org", "snippet": "\u2026 CNN, one of the deep learning methods\u2014is proposed for feature extraction in this study. \nCNN is considered as another type of multilayer perceptron since it used more than one layer of \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4425850600288158180&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:5AEg-6vHaz0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4425850600288158180&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Modelling biomass and plant diversity in grasslands across sites and time with deep learning and Sentinel-2 satellite images", "title_link": "https://ui.adsabs.harvard.edu/abs/2021AGUFM.B11A..07M/abstract", "publication_info": "J Muro, A Linstadter, L Schwarz\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2021 - ui.adsabs.harvard.edu", "snippet": "\u2026 Understanding the linkages between biomass production and biodiversity in grasslands \nis critical to evaluate the effects of management practices across environmental gradients. \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Deep learning soundscape classification and remotely sensed forest structure reveal landscape patterns in ecoacoustics", "title_link": "https://ui.adsabs.harvard.edu/abs/2021AGUFM.B13A..04Q/abstract", "publication_info": "C Quinn, P Burns, M Clark\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2021 - ui.adsabs.harvard.edu", "snippet": "\u2026 Ecoacoustic developments provide opportunities for landscape-scale biodiversity and human \nimpact research using low-cost and widely applicable tools and have resulted in an influx \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Automated facial recognition for wildlife that lack unique markings: A deep learning approach for brown bears", "title_link": "https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.6840", "publication_info": "M Clapham, E Miller, M Nguyen\u2026\u00a0- Ecology and\u00a0\u2026, 2020 - Wiley Online Library", "snippet": "\u2026 We apply deep learning approaches of facial recognition using object detection, landmark \u2026 \na replicable methodology for applying deep learning methods of facial recognition applicable \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11305830382410921680&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:0PZr-tRg5pwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11305830382410921680&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Detecting Dams with Satellite Imagery and Deep Learning for a More Sustainable Freshwater Future", "title_link": "https://ui.adsabs.harvard.edu/abs/2019AGUFMPA33A..04M/abstract", "publication_info": "L Mandle, R Sharp, C Weil\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2019 - ui.adsabs.harvard.edu", "snippet": "\u2026 This infrastructure has had immense environmental impacts, both on freshwater biodiversity \nand on hydrological ecosystem services. Knowing the locations of dams and reservoirs is a \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=13809891741202168197&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=13809891741202168197&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Expanding NEON biodiversity surveys with new instrumentation and machine learning approaches", "title_link": "https://esajournals.onlinelibrary.wiley.com/doi/abs/10.1002/ecs2.3795", "publication_info": "J Kitzes, R Blake, S Bombaci, M Chapman\u2026\u00a0- \u2026, 2021 - Wiley Online Library", "snippet": "\u2026 biodiversity surveys within the NEON project and previous research at the intersection of \nbiodiversity\u2026 fruitful future paths for automated biodiversity measurement at NEON sites: acoustic \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:NNeCjo1sC9gJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=15567655892173379380&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15567655892173379380&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Comparison of unsupervised learning methods for natural image processing", "title_link": "https://www.researchgate.net/profile/Cristina-Olaverri-Monreal/publication/335046209_Comparison_of_Unsupervised_Learning_Methods_for_Natural_Image_Processing/links/5d4c1fa1299bf1995b6fa672/Comparison-of-Unsupervised-Learning-Methods-for-Natural-Image-Processing.pdf", "publication_info": "W W\u00f6ber, PD Tibihika, C Olaverri-Monreal\u2026\u00a0- Biodiversity\u00a0\u2026, 2019 - researchgate.net", "snippet": "\u2026 In this work, we discuss unsupervised learning algorithms in terms of explainability, performance \nand theoretical restrictions in context of known deep learning restrictions (Marcus 2018, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11297551631874942087&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:h2SKKVr3yJwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11297551631874942087&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A Deep Learning Approach for Mapping Distribution of Forest Canopy Height Across Africa from Radar Imagery", "title_link": "https://ui.adsabs.harvard.edu/abs/2019AGUFMGC53B..07X/abstract", "publication_info": "L Xu, S Saatchi\u00a0- AGU Fall Meeting Abstracts, 2019 - ui.adsabs.harvard.edu", "snippet": "\u2026 As the proxy of vegetation living biomass and indicator of biodiversity, canopy height is a \u2026 \ninternal texture generated from original SAR data using deep-learning model is key to the more \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=8015034164976559385&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=8015034164976559385&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A Machine Learning Approach to Biodiversity Time Series Analysis", "title_link": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3520735", "publication_info": "R Paul, S Kumar\u00a0- A Machine Learning Approach to Biodiversity\u00a0\u2026, 2019 - papers.ssrn.com", "snippet": "\u2026 There is an alternative approach of using deep learning algorithms for processing time \nseries data. LSTM is one among them where we can preserve the features of training data for a \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:dORsk-4RDbQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=12974045817897542772&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12974045817897542772&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Novel ensemble approach of deep learning neural network (DLNN) model and particle swarm optimization (PSO) algorithm for prediction of gully erosion susceptibility", "title_link": "https://www.mdpi.com/844528", "publication_info": "SS Band, S Janizadeh, S Chandra Pal, A Saha\u2026\u00a0- Sensors, 2020 - mdpi.com", "snippet": "This study aims to evaluate a new approach in modeling gully erosion susceptibility (GES) \nbased on a deep learning neural network (DLNN) model and an ensemble particle swarm \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14257194661708980017&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=YnCDEY0AAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=14257194661708980017&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Application of Deep Learning in Deforestation Control and Prediction of Forest Fire Calamities", "title_link": "https://www.taylorfrancis.com/chapters/edit/10.1201/9781003133681-14/application-deep-learning-deforestation-control-prediction-forest-fire-calamities-muskan-goenka-ramchandra-mangrulkar", "publication_info": "M Goenka, RS Mangrulkar\u00a0- \u2026\u00a0Learning and Deep Learning\u00a0\u2026, 2021 - taylorfrancis.com", "snippet": "\u2026 Forest ecosystems are a critical component of the world\u2019s biodiversity as the living world is \ndirectly dependent on them than other ecosystems. Security and safety is the top priority when \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:3DtrNpzIYy4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=3342735921692490716&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3342735921692490716&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep Learning Enhances the Detection of Breeding Birds in UAV Images", "title_link": "https://ui.adsabs.harvard.edu/abs/2021EGUGA..2312157K/abstract", "publication_info": "B Kellenberger, T Veen, E Folmer\u2026\u00a0- EGU General Assembly\u00a0\u2026, 2021 - ui.adsabs.harvard.edu", "snippet": "\u2026 In this work, we automate the detection process with deep learning [4]. We focus on \u2026 Monitoring \ntheir abundance provides invaluable insights into biodiversity in this area [7]. In a first step\u2026", "cited_by": "https://scholar.google.com/scholar?q=related:zU4YTJcSeS0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=3276670644914769613&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3276670644914769613&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A Deep Learning-based Computer Vision Approach for Comparative Monarch Butterfly Phenotype Identification in Citizen Science", "title_link": "https://faseb.onlinelibrary.wiley.com/doi/abs/10.1096/fasebj.2021.35.S1.05504", "publication_info": "T Chen\u00a0- The FASEB Journal, 2021 - Wiley Online Library", "snippet": "\u2026 a baseline deep-learning classification model to serve as a tool for differentiating monarch \nbutterflies and its various look-alikes. We seek to contribute to the study of biodiversity and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14239956490540098166&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?cluster=14239956490540098166&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14239956490540098166&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Urban form and composition of street canyons: A human-centric big data and deep learning approach", "title_link": "https://www.sciencedirect.com/science/article/pii/S0169204618313550", "publication_info": "A Middel, J Lukasczyk, S Zakrzewski, M Arnold\u2026\u00a0- Landscape and Urban\u00a0\u2026, 2019 - Elsevier", "snippet": "\u2026 We employed a scalable deep learning framework to segment 90-degree field of view GSV \nimage cubes into six classes: sky, trees, buildings, impervious surfaces, pervious surfaces, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13278942496375458986&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:qkxMedhHSLgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13278942496375458986&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Aspen detection in boreal forests: Capturing a key component of biodiversity using airborne hyperspectral, lidar, and UAV data", "title_link": "https://ui.adsabs.harvard.edu/abs/2020EGUGA..2221268K/abstract", "publication_info": "T Kumpula, A Viinikka, J M\u00e4yr\u00e4\u2026\u00a0- EGU General\u00a0\u2026, 2020 - ui.adsabs.harvard.edu", "snippet": "\u2026 for biodiversity. Aspen is a keystone species, hosting a range of endangered species, hence \nhaving a high importance in maintaining forest biodiversity\u2026 ) and deep learning methods (3D \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=4951126420024813481&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=4951126420024813481&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Image-based Plant Species Identification with Deep Convolutional Neural Networks.", "title_link": "http://ceur-ws.org/Vol-1866/paper_174.pdf", "publication_info": "M Lasseck\u00a0- CLEF (Working Notes), 2017 - ceur-ws.org", "snippet": "\u2026 This paper presents deep learning techniques for image-\u2026 [3] for education, biodiversity \nmonitoring and the collection of \u2026 to conditions of real-world biodiversity monitoring scenarios at a \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3940586069223501641&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:SW_r3ibGrzYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3940586069223501641&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Evolutionary history of Native Americans drown by deep learning \u0430pproach", "title_link": "https://elibrary.ru/item.asp?id=38087539", "publication_info": "O Dolgova, I Maceda, O Lao\u00a0- Biodiversity: Genomics and Evolution\u00a0\u2026, 2018 - elibrary.ru", "snippet": "\u2026 on coupling of Deep Learning with Approximate Bayesian \u2026 nine Native American populations \nforming Deep Learning system of four \u2026 computation and Deep Learning development were \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:3Q8GIqZUH98J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=16077662267248087005&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16077662267248087005&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Detecting a keystone species European aspen in boreal forests with airborne hyperspectral, LiDAR and UAV data with machine learning methods", "title_link": "https://ui.adsabs.harvard.edu/abs/2021EGUGA..2316273K/abstract", "publication_info": "T Kumpula, J M\u00e4yr\u00e4, A Kuzmin\u2026\u00a0- EGU General\u00a0\u2026, 2021 - ui.adsabs.harvard.edu", "snippet": "\u2026 forest biodiversity. European aspen (Populus tremula L.) is a minor deciduous tree species \nwith a high importance in maintaining biodiversity \u2026 learning and deep learning classification \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=15483642867326228049&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=15483642867326228049&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Ecoacoustic recordings capture animal population and community changes over time", "title_link": "https://ui.adsabs.harvard.edu/abs/2020AGUFMB070...07R/abstract", "publication_info": "D Rappaport, DC Morton, A Swain\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2020 - ui.adsabs.harvard.edu", "snippet": "\u2026 our understanding of global biodiversity. Ecoacoustics is an \u2026 , and another using deep \nlearning to detect the acoustic \u2026 Importantly, biomass was not a robust proxy for biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=17155323219227376433&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=17155323219227376433&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Rapid field identification of CITES timber species by deep learning", "title_link": "https://www.sciencedirect.com/science/article/pii/S2666719320300169", "publication_info": "K Olschofsky, M K\u00f6hl\u00a0- Trees, Forests and People, 2020 - Elsevier", "snippet": "\u2026 We present a new method based on a deep learning approach that facilitates the \u2026 the potential \nof simple applicable pre trained deep learning for the operational field inspection of timber \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5666312110090034709&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:FR5pvNfIok4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5666312110090034709&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Reducing the Barriers of Acquiring Ground-truth from Biodiversity Rich Audio Datasets Using Intelligent Sampling Techniques", "title_link": "https://www.researchgate.net/profile/Jacob_Ayers3/publication/360555167_Reducing_the_Barriers_of_Acquiring_Ground-truth_from_Biodiversity_Rich_Audio_Datasets_Using_Intelligent_Sampling_Techniques/links/627d7fd337329433d9ac52af/Reducing-the-Barriers-of-Acquiring-Ground-truth-from-Biodiversity-Rich-Audio-Datasets-Using-Intelligent-Sampling-Techniques.pdf", "publication_info": "J Ayers, S Perry, V Tiwari, M Blue, N Balaji\u2026 - researchgate.net", "snippet": "\u2026 animals in camera-trap images with deep learning. Proceedings of the National Academy of \n\u2026 Identifying animal species in camera trap images using deep learning and citizen science. \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:oTktdj6VKA8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Aspen detection in boreal forests: Capturing a key component of biodiversity with airborne hyperspectral, lidar, and UAV data using machine learning and 3D\u00a0\u2026", "title_link": "https://ui.adsabs.harvard.edu/abs/2020AGUFMB042...03K/abstract", "publication_info": "T Kumpula, J M\u00e4yr\u00e4, A Viinikka\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2020 - ui.adsabs.harvard.edu", "snippet": "\u2026 for biodiversity. Aspen is a keystone species, hosting a range of endangered species, hence \nhaving a high importance in maintaining forest biodiversity\u2026 ) and deep learning methods (3D \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=10718298038548865709&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=10718298038548865709&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Using deep learning to classify images of wall lizards", "title_link": "https://repositorio-aberto.up.pt/bitstream/10216/138247/2/519158.pdf", "publication_info": "CL Pinho - 2021 - repositorio-aberto.up.pt", "snippet": "\u2026 of describing the Earth\u2019s vanishing biodiversity. In this context, \u2026 of machine learning, with \ndeep learning algorithms based on \u2026 In this work, we took a deep learning approach to classify \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=15005492435892111880&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=15005492435892111880&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Cloud computing for deep learning analytics: A survey of current trends and challenges.", "title_link": "https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=09765697&AN=122708775&h=uiz7%2B%2F27vq%2BCu5suoi%2Ffc6PwPXPTPBxJIsKoIpaXT7kHj931EaXr2OcX02ECCYFd9%2FK%2FFX6XG3A4VOF%2BQM6nNA%3D%3D&crl=c", "publication_info": "A Saiyeda, MA Mir\u00a0- International Journal of Advanced\u00a0\u2026, 2017 - search.ebscohost.com", "snippet": "\u2026 for deep learning analytics as it provides servers, storage and networking resources. It provides \nscalability, processing, storage and analytics resources. Deep learning \u2026 of deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2005452856607399173&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:BV3ga7_M1BsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2005452856607399173&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Environmental factors as indicators of dissolved oxygen concentration and zooplankton abundance: Deep learning versus traditional regression approach", "title_link": "https://www.sciencedirect.com/science/article/pii/S1470160X18307489", "publication_info": "A Banerjee, M Chakrabarty, N Rakshit, AR Bhowmick\u2026\u00a0- Ecological\u00a0\u2026, 2019 - Elsevier", "snippet": "Presence of optimal levels of dissolved oxygen (above critical level of 4.5 mg L \u22121 ) and \npresence of zooplankton community are indicators of good water quality of an aquatic \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3607901233933205551&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:L0BIiQ7XETIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3607901233933205551&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Detecting of natural forest to oil palm conversions in tropical wetlands based on sentinel imagery using deep learning", "title_link": "http://essay.utwente.nl/88924/", "publication_info": "F Muzakki - 2021 - essay.utwente.nl", "snippet": "\u2026 tropical wetlands is dangerous for humans and biodiversity. Their capability to store carbon \n\u2026 accuracy using different sampling techniques and deep learning models. Moreover, the \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comhttp://scholar.googleusercontent.com/scholar?q=cache:bKFeNI3iScoJ:scholar.google.com/+biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Source separation in ecoacoustics: a roadmap towards versatile soundscape information retrieval", "title_link": "https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.141", "publication_info": "TH Lin, Y Tsao\u00a0- Remote Sensing in Ecology and Conservation, 2020 - Wiley Online Library", "snippet": "\u2026 With the recent advances of deep learning, the model-based \u2026 to evaluate the contributions \nfrom biodiversity and anthropogenic \u2026 of ecological hypotheses and deep learning can realize a \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3327124851026909752&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:OFrVlGxSLC4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3327124851026909752&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "The automatic identification of butterfly species using deep learning methodologies", "title_link": "https://openaccess.mef.edu.tr/handle/20.500.11779/1688", "publication_info": "T Kara, S Emel - 2020 - openaccess.mef.edu.tr", "snippet": "\u2026 like machine learning, deep learning and image processing, \u2026 world resources, conservation \nof biodiversity, and sustainable \u2026 They did this work with deep learning approaches such as \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:3113_yJqIPsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[BOOK][B] BIOfid, a Platform to Enhance Accessibility of Biodiversity Data", "title_link": "https://www.researchgate.net/profile/Gerwin-Kasperek/publication/327940813_BIOfid_a_Platform_to_Enhance_Accessibility_of_Biodiversity_Data/links/5c9bbb2e92851cf0ae9c6ed6/BIOfid-a-Platform-to-Enhance-Accessibility-of-Biodiversity-Data.pdf", "publication_info": "C Weiland, C Driller, M Koch, M Schmidt, G Abrami\u2026 - 2018 - researchgate.net", "snippet": "\u2026 Improving acoustic monitoring of biodiversity using deep learning-based source separation \nalgorithms ...... 67 Acoustic sensor networks and machine learning: scalable ecological data \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=1371911551690336746&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=1371911551690336746&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Modeling the response of ecological service value to land use change through deep learning simulation in Lanzhou, China", "title_link": "https://www.sciencedirect.com/science/article/pii/S0048969721040535", "publication_info": "J Liu, B Xiao, J Jiao, Y Li, X Wang\u00a0- Science of the Total Environment, 2021 - Elsevier", "snippet": "\u2026 Deep learning is used to extract spatiotemporal features to improve \u2026 A coupled deep learning \nand cellular automata model was designed to \u2026 Wetland loss and biodiversity conservation \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5890837823962131880&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:qK2yNsp1wFEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5890837823962131880&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning-based extreme heatwave forecast", "title_link": "https://arxiv.org/abs/2103.09743", "publication_info": "V Jacques-Dumas, F Ragone, P Borgnat\u2026\u00a0- arXiv preprint arXiv\u00a0\u2026, 2021 - arxiv.org", "snippet": "\u2026 Because of the impact of extreme heat waves and heat domes on society and biodiversity, \u2026 \nThe present work explores the use of deep learning architectures, trained using outputs of a \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11831597010570856603&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:m0imbMtGMqQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11831597010570856603&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Individual palm tree detection using deep learning on RGB imagery to support tree inventory", "title_link": "https://www.mdpi.com/866628", "publication_info": "M Culman, S Delalieux, K Van Tricht\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "\u2026 A deep learning architecture that was based on convolutional neural networks (CNN) was \n\u2026 that are based on deep learning leverage image understanding from remote sensing data. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6580926150925504540&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:HFD-jnclVFsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6580926150925504540&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Using Unsupervised Artificial Neural Networks to Detect Sibling Species: A case in Myxomycetes", "title_link": "https://biss.pensoft.net/article/37255/download/pdf/", "publication_info": "F Pando, I Heredia, L Lloret\u00a0- Biodiversity Information Science and\u00a0\u2026, 2019 - biss.pensoft.net", "snippet": "\u2026 In this presentation, we explore deep learning techniques (LeCun et al. 2015), particularly \nhow those developed in recent years could contribute to the study of species distribution (see \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:TK9LDWR33LwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=13608883445610295116&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13608883445610295116&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep corals, deep learning: moving the deep net towards real-time image annotation", "title_link": "https://pure.qub.ac.uk/en/publications/deep-corals-deep-learning-moving-the-deep-net-towards-real-time-i", "publication_info": "LA Henry, SS Mukherjee, NM Robertson\u2026\u00a0- \u2026\u00a0Symposium on Deep\u00a0\u2026, 2016 - pure.qub.ac.uk", "snippet": "The mismatch between human capacity and the acquisition of Big Data such as Earth imagery \nundermines commitments to Convention on Biological Diversity (CBD) and Aichi targets. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15098901516675074409&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:aUkGmO4SitEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Mobile-based deep learning models for banana diseases detection", "title_link": "https://arxiv.org/abs/2004.03718", "publication_info": "S Sanga, V Mero, D Machuve\u2026\u00a0- arXiv preprint arXiv\u00a0\u2026, 2020 - arxiv.org", "snippet": "\u2026 In this work we evaluated the capability of deep learning models and transfer learning \ntechniques in crop diseases diagnostics. We deployed the model on mobile phone with capability \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16741357482765745473&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:QX0UWu4_VegJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16741357482765745473&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Bird Species Recognition Techniques Based On Deep Learning Methods-A Survey", "title_link": "http://www.ijsrcsams.com/images/stories/Past_Issue_Docs/ijsrcsamsv8i3p16.pdf", "publication_info": "K Annalakshmi, IE Shanthi - ijsrcsams.com", "snippet": "\u2026 an important task in ecosystem monitoring and biodiversity preservation. Recognition of bird \n\u2026 classified using Hidden Markov Model (HMM) which is based on deep learning techniques. \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:grYzixwNJxEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=1235971038982157954&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1235971038982157954&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A deep learning approach for burned area segmentation with Sentinel-2 data", "title_link": "https://www.mdpi.com/781914", "publication_info": "L Knopp, M Wieland, M R\u00e4ttich, S Martinis\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "\u2026 ecosystems and can have positive effects on biodiversity and natural regeneration [1]. \u2026 \nforest stands [3], impair forest health and biodiversity [4] and emit aerosols and other greenhouse \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6297950369947286326&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Nnu_VX7QZlcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6297950369947286326&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Editorial for Research Topic: Applications of Machine Learning to Evolutionary Ecology Data", "title_link": "https://www.frontiersin.org/articles/10.3389/fevo.2021.797319/pdf", "publication_info": "J Morimoto, A Ponchon, G Sofronov\u2026\u00a0- Frontiers in Ecology and\u00a0\u2026, 2021 - frontiersin.org", "snippet": "\u2026 to facilitate taxonomic identification and biodiversity survey, find \u2026 Using a clever combination \nof a complex deep learning \u2026 the major bottleneck in biodiversity assessments of insects (ie, \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:hnpE40Mt2sEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=13968526963841989254&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13968526963841989254&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Handcrafted features and late fusion with deep learning for bird sound classification", "title_link": "https://www.sciencedirect.com/science/article/pii/S1574954118302991", "publication_info": "J Xie, M Zhu\u00a0- Ecological Informatics, 2019 - Elsevier", "snippet": "\u2026 We investigate acoustic features, visual features, and deep learning for bird species \u2026 \nThen, we investigate deep learning techniques to classify bird calls. To further improve the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11059103964516164214&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:dqIZS3bUeZkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11059103964516164214&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep Learning Methods for Extracting Habitat Summaries from Remotely Sensed Data for Species Distribution Modeling", "title_link": "https://ui.adsabs.harvard.edu/abs/2020AGUFMB071...05H/abstract", "publication_info": "L Hopkins, U Zaragoza, WK Wong\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2020 - ui.adsabs.harvard.edu", "snippet": "\u2026 Given the advancements in computer vision due to deep learning, features extracted by \ndeep neural networks have the potential to characterize habitats better than methods currently \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=2262481431697595875&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=2262481431697595875&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning enabled detection of low incidence plant disease with integrated proximal and remote sensing", "title_link": "https://ui.adsabs.harvard.edu/abs/2020AGUFMB004.0004G/abstract", "publication_info": "K Gold, F Romero, HR Kerner\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2020 - ui.adsabs.harvard.edu", "snippet": "\u2026 ,\" foliar fungal disease in vineyards with deep learning and proximal sensing derived training \n\u2026 Using recently developed deep learning models to quantify disease intensity from the side \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=5861146940892584781&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=5861146940892584781&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automatic detection of impervious surfaces from remotely sensed data using deep learning", "title_link": "https://www.mdpi.com/1223752", "publication_info": "JR Parekh, A Poortinga, B Bhandari, T Mayer, D Saah\u2026\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 In this paper, we train deep learning neural networks using \u2026 performance of different deep \nlearning neural network architectures, \u2026 above, is a deep learning neural network that combines \u2026", "cited_by": "https://scholar.google.com/scholar?cites=767108270655297694&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=8mTbUxkAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=767108270655297694&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for automated analysis of fish abundance: the benefits of training across multiple habitats", "title_link": "https://link.springer.com/article/10.1007/s10661-020-08653-z", "publication_info": "EM Ditria, M Sievers, S Lopez-Marcano\u2026\u00a0- Environmental\u00a0\u2026, 2020 - Springer", "snippet": "\u2026 performance of the deep learning model will depend on the environment, or domain, it was \ntrained on (Kalogeiton et al. 2016). Here, we test the potential for deep learning algorithms to \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16892779970211360492&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:7C5IkeE1b-oJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16892779970211360492&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning-based approach in plant species identification/Tan Jing Wei", "title_link": "http://studentsrepo.um.edu.my/id/eprint/11621", "publication_info": "JW Tan - 2018 - studentsrepo.um.edu.my", "snippet": "\u2026 in various fields including in biology and biodiversity. Deep learning is an emerging area in \nthe \u2026 The features were then extracted by using one of the deep learning approaches which is \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:gDLRnBg7ZsgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=14440294232106283648&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14440294232106283648&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Wild animal survey using UAS imagery and deep learning: modified Faster R-CNN for kiang detection in Tibetan Plateau", "title_link": "https://www.sciencedirect.com/science/article/pii/S0924271620302409", "publication_info": "J Peng, D Wang, X Liao, Q Shao, Z Sun, H Yue\u2026\u00a0- ISPRS Journal of\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 Among these algorithms, deep learning techniques achieve \u2026 Based on a typical deep \nlearning pipeline, faster region \u2026 of UAS and deep learning techniques can enable automatic/\u2026", "cited_by": "https://scholar.google.com/scholar?cites=4102062915418183517&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:XdfN53x07TgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4102062915418183517&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Oil palm plantation mapping from high-resolution remote sensing images using deep learning", "title_link": "https://www.tandfonline.com/doi/abs/10.1080/01431161.2019.1681604", "publication_info": "R Dong, W Li, H Fu, L Gan, L Yu\u2026\u00a0- International Journal of\u00a0\u2026, 2020 - Taylor & Francis", "snippet": "\u2026 In order to obtain finer oil palm plantation maps from high spatial-resolution satellite \nimages, we proposed a novel deep learning-based semantic segmentation approach, named \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11061477981650824057&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=oHSjwDgAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=11061477981650824057&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Uncovering Illegal Wildlife Trade on Social Media: Automatic Data Collection, Deep Learning Filters and Identification", "title_link": "https://researchportal.helsinki.fi/en/publications/uncovering-illegal-wildlife-trade-on-social-media-automatic-data-", "publication_info": "CA Fink, T Hiippala, HTO Tenkanen\u2026\u00a0- European\u00a0\u2026, 2018 - researchportal.helsinki.fi", "snippet": "\u2026 Illegal wildlife trade is one of the biggest threats to biodiversity \u2026 Machine-learning, and \nespecially deep learning, has seen a \u2026 Deep learning describes a machine-learning approach in \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=12389409061210373074&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=12389409061210373074&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Image Recognition to Enhance the Value of Collections", "title_link": "https://search.proquest.com/openview/34f7acdbc07cbb90c19692639a56c848/1?pq-origsite=gscholar&cbl=2049297", "publication_info": "M Caspers\u00a0- Biodiversity Information Science and Standards, 2018 - search.proquest.com", "snippet": "\u2026 With an estimated 44 million objects, the collection of Naturalis Biodiversity Center has \u2026 \nsegmentation of those images to \u201cfeed\u201d deep learning-based image recognition with images of \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=14613801409178151726&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=14613801409178151726&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep Learning for Forest Plantation Mapping in Godavari Districts of Andhra Pradesh, India", "title_link": "https://vtechworks.lib.vt.edu/handle/10919/100058", "publication_info": "S More, A Karpatne, RH Wynne\u2026\u00a0- EARTH DAY, KDD\u00a0\u2026, 2019 - vtechworks.lib.vt.edu", "snippet": "\u2026 forest have adverse impacts on biodiversity. Mapping small-\u2026 Pradesh, India using deep \nlearning methods. Remotely \u2026 We compare the performance of deep learning methods with \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comhttps://scholar.googleusercontent.com/scholar?q=cache:VFjQuXIgCzsJ:scholar.google.com/+biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Taxon and trait recognition from digitized herbarium specimens using deep convolutional neural networks", "title_link": "https://www.tandfonline.com/doi/abs/10.1080/23818107.2018.1446357", "publication_info": "S Younis, C Weiland, R Hoehndorf, S Dressler\u2026\u00a0- Botany\u00a0\u2026, 2018 - Taylor & Francis", "snippet": "\u2026 There are many types of deep-learning networks but in our experiment we use \u2026 Biodiversity \nand Climate Research Center (SBIK-F) with a focus on African savannas and biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5561768100702709834&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Suh7vZ5eL00J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5561768100702709834&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] 4. What are the challenges for biodiversity?", "title_link": "https://www.researchgate.net/profile/Agathe-Euzen/publication/324531362_The_Ocean_revealed_-_book/data/5ad377730f7e9b285935f2c4/170922-OcCan-EN-BD.pdf#page=27", "publication_info": "D Mouillot\u00a0- The Ocean - researchgate.net", "snippet": "\u2026 recognize species using increasingly powerful algorithms (deep learning). For example, the \n\u2026 cm) will only strengthen this automated monitoring of marine biodiversity in the digital era. \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:v2SQmQ-67pkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=11092007508423763135&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11092007508423763135&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Challenges in Applying Audio Classification Models to Datasets Containing Crucial Biodiversity Information", "title_link": "https://kastner.ucsd.edu/wp-content/uploads/2021/08/admin/icmlclimatechangeai21-challenges.pdf", "publication_info": "J Ayers, Y Jandali, YJ Hwang, G Steinberg, E Joun\u2026 - kastner.ucsd.edu", "snippet": "\u2026 of climate change on biodiversity. Hardware costs, human \u2026 field that contain crucial biodiversity \ninformation that otherwise \u2026 camera trap images using deep learning and citizen science. \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:06uC2RQoCLkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=13332950766844029907&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13332950766844029907&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Notes of Life: A platform for recording species observations driven by artificial intelligence.", "title_link": "https://go.gale.com/ps/i.do?id=GALE%7CA646393868&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=25350897&p=AONE&sw=w", "publication_info": "C Lin, J Wang, L Ji\u00a0- Biodiversity Information Science and Standards, 2019 - go.gale.com", "snippet": "\u2026 of biodiversity data, especially the large number of species images. It has been a new trend \nand hot topic on how to utilize artificial intelligence to mine big biodiversity \u2026 deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=15337293986537327982&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=15337293986537327982&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Chimera: A deep-learning approach for fusing multi-sensor data for forest classification and structural estimation", "title_link": "https://ui.adsabs.harvard.edu/abs/2019AGUFM.B21A..04C/abstract", "publication_info": "T Chang, B Rasmussen, BG Dickson\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2019 - ui.adsabs.harvard.edu", "snippet": "\u2026 In this talk we describe a new approach to simultaneously classify forest land cover type \nand estimate continuous forest structure metrics using a deep learning model ensemble. Our \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=12116627417711852840&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=12116627417711852840&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for tree crown detection in tropical forest", "title_link": "https://ieeexplore.ieee.org/abstract/document/9001817/", "publication_info": "Z Roslan, Z Awang, MN Husen\u2026\u00a0- 2020 14th\u00a0\u2026, 2020 - ieeexplore.ieee.org", "snippet": "\u2026 With the advancement of deep learning network, the proposed methodology uses the state-\u2026 \nuse of deep learning object detection model in airborne tree mapping, biodiversity surveys, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7700625784764257518&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:7lQWAVoe3moJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "A workbench for species identification based on images and deep learning techniques", "title_link": "https://search.proquest.com/openview/d227f3f94e0f54ab073d9cc11579b750/1?pq-origsite=gscholar&cbl=2049297", "publication_info": "I Heredia, L Lloret, J Marco\u2026\u00a0- Biodiversity Information\u00a0\u2026, 2017 - search.proquest.com", "snippet": "We are currently studying the feasibility of applying deep learning techniques to natural \nsciences. In this contribution we will show our recent advances with an easy plug-and-play \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=14682964610523013777&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=14682964610523013777&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A deep learning based forest fire detection approach using UAV and YOLOv3", "title_link": "https://ieeexplore.ieee.org/abstract/document/8850815/", "publication_info": "Z Jiao, Y Zhang, J Xin, L Mu, Y Yi\u2026\u00a0- 2019 1st International\u00a0\u2026, 2019 - ieeexplore.ieee.org", "snippet": "\u2026 They can provide habitat for animals, maintain biodiversity and purify the air. Known as the \n\u201cLung of the Earth\u201d, the forest has rich natural and social economic values. However, current \u2026", "cited_by": "https://scholar.google.com/scholar?cites=422267633806377453&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:7YEs-Swy3AUJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "ANIS:\u201cAccuracy of ecological Niches Improved by Satellite\u201d", "title_link": "https://elibrary.ru/item.asp?id=37287972", "publication_info": "C Eric, M Morgan, G Antoine, P Andrew\u00a0- \u2026\u00a0RESEARCH OF BIODIVERSITY\u00a0\u2026, 2018 - elibrary.ru", "snippet": "\u2026 The idea is also to make the best of the recent developments in deep learning technologies \n\u2026 Biodiversity Information Facility) in order to initiate a new generation of ENMs. Deep learning \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[PDF][PDF] AI-based Identification of Plant Photographs from Herbarium Specimens", "title_link": "https://biss.pensoft.net/article/73751/download/pdf/", "publication_info": "H Go\u00ebau, P Bonnet, A Joly\u00a0- Biodiversity Information Science and\u00a0\u2026, 2021 - biss.pensoft.net", "snippet": "\u2026 Automated plant identification has recently improved significantly due to advances in \ndeep learning and the availability of large amounts of field photos. As an illustration, the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11415858160212241436&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:HOyxTYNGbZ4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11415858160212241436&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning approaches for tree species diversity mapping in a tropic wetland using airborne LiDAR and high resolution remote sensing images", "title_link": "https://ui.adsabs.harvard.edu/abs/2019AGUFM.B14A..06S/abstract", "publication_info": "Y Sun, Q Xin, J Huang\u00a0- AGU Fall Meeting Abstracts, 2019 - ui.adsabs.harvard.edu", "snippet": "\u2026 Three different deep learning methods (AlexNet, VGG16 and ResNet50) are modified to classify \n\u2026 , the deep learning based solution shows the potential in tree species diversity mapping. \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=4773786354673869640&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=4773786354673869640&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Fusion of Sentinel-2 and Sentinel-3 Imagery via Deep Learning", "title_link": "https://ui.adsabs.harvard.edu/abs/2019AGUFM.B11F2394M/abstract", "publication_info": "R Mukherjee, D Liu\u00a0- AGU Fall Meeting Abstracts, 2019 - ui.adsabs.harvard.edu", "snippet": "\u2026 Recently, deep learning superresolution algorithms have \u2026 In this research, a deep learning \nsuperresolution model is \u2026 The deep learning model is trained to learn the spatial feature \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=15147114845003955362&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=15147114845003955362&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Satellite Data Fusion of Multiple Observed XCO2 using Compressive Sensing and Deep Learning", "title_link": "https://ui.adsabs.harvard.edu/abs/2019AGUFM.B11F2400H/abstract", "publication_info": "M Halem, SSL Chukkapalli\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2019 - ui.adsabs.harvard.edu", "snippet": "\u2026 Recent advances in Compressive Sensing (CS) when combined with Deep Learning (DL) \nand have profound potential impacts for recovering, discovering, extracting and enhancing \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=3494364126804232680&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=3494364126804232680&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Recognition of endangered pantanal animal species using deep learning methods", "title_link": "https://ieeexplore.ieee.org/abstract/document/8489369/", "publication_info": "MS de Arruda, G Spadon, JF Rodrigues\u2026\u00a0- \u2026\u00a0Joint Conference on\u00a0\u2026, 2018 - ieeexplore.ieee.org", "snippet": "\u2026 (eg, cattle ranching, agriculture, tourism) with the conservation of the biodiversity [3]. \nHowever, getting to know the biodiversity present in the vast area of Pantanal comes to be a big \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7359426517179450734&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:bkUS62zvIWYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7359426517179450734&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Leaf Classifying Model in Crop Identification using Machine Learning Algorithm", "title_link": "https://www.academia.edu/download/65361848/IRJET_V7I1293.pdf", "publication_info": "G Muneeswari - 2020 - academia.edu", "snippet": "\u2026 image processing and deep learning through convolutional \u2026 and identifying crops of the \nbiodiversity beds using Anaconda\u2019\u2026 of a deep learning model using Random Forest Algorithm. \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:Lgf2TtYLk7YJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Deep learning in forest structural parameter estimation using airborne lidar data", "title_link": "https://ieeexplore.ieee.org/abstract/document/9300163/", "publication_info": "H Liu, X Shen, L Cao, T Yun, Z Zhang\u2026\u00a0- IEEE Journal of\u00a0\u2026, 2020 - ieeexplore.ieee.org", "snippet": "\u2026 The novel deep learning algorithm has the potential to be a promising \u2026 a deep learning-based \nalgorithm (Deep-RBN) that combined the fully connected network (FCN) deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14190455430085806899&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:MwtHhweg7sQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14190455430085806899&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automatic classification of trees using a UAV onboard camera and deep learning", "title_link": "https://arxiv.org/abs/1804.10390", "publication_info": "M Onishi, T Ise\u00a0- arXiv preprint arXiv:1804.10390, 2018 - arxiv.org", "snippet": "\u2026 UAV and a publicly available package for deep learning, we constructed a machine vision \u2026 \ndeep learning can use full feature information, so even if we use digital images, deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7397219030600810036&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:NH64JIQzqGYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7397219030600810036&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Using Deep Learning to Monitor Coral Reef Health", "title_link": "https://mazziotti.uchicago.edu/journal/narayan_r.pdf", "publication_info": "R Narayan - mazziotti.uchicago.edu", "snippet": "\u2026 or convolutional neural networks (CNNs), a type of deep learning architecture most often \nused in image classification which generates functions that map the features in an input image \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:NzaDjys4xNwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Deep learning for coral classification", "title_link": "https://www.sciencedirect.com/science/article/pii/B9780128113189000211", "publication_info": "A Mahmood, M Bennamoun, S An, F Sohel\u2026\u00a0- Handbook of neural\u00a0\u2026, 2017 - Elsevier", "snippet": "\u2026 a rapid decline in our planet's marine biodiversity [5]. In order \u2026 of deep learning for automatic \nannotation of coral reef images. \u2026 Section 21.4 presents a brief introduction of deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5324377336182479570&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:0hpMPfr840kJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5324377336182479570&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Application of deep learning techniques for determining the spatial extent and classification of seagrass beds, Trang, Thailand", "title_link": "https://www.degruyter.com/document/doi/10.1515/bot-2018-0017/html", "publication_info": "T Yamakita, F Sodeyama, N Whanpetch\u2026\u00a0- Botanica\u00a0\u2026, 2019 - degruyter.com", "snippet": "\u2026 Chapter 3: Status, trends and future dynamics of biodiversity and ecosystems underpinning \n\u2026 The IPBES regional assessment report on biodiversity and ecosystem services for Asia and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15386880631165763089&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ET75LWkuidUJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15386880631165763089&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Developing deep learning models to automate rosewood tree species identification for CITES designation and implementation", "title_link": "https://www.degruyter.com/document/doi/10.1515/hf-2020-0006/html", "publication_info": "T He, Y Lu, L Jiao, Y Zhang, X Jiang, Y Yin\u00a0- Holzforschung, 2020 - degruyter.com", "snippet": "\u2026 deep learning model were analyzed, and the representative wood anatomical features that \nwere activated by the deep learning \u2026 train reliable and applicable deep learning models. The \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3542022803284501837&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:TSUbIPnKJzEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3542022803284501837&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Predicting tree species from 3D laser scanning point clouds using deep learning", "title_link": "https://www.frontiersin.org/articles/10.3389/fpls.2021.635440/full", "publication_info": "D Seidel, P Annigh\u00f6fer, A Thielman\u2026\u00a0- Frontiers in Plant\u00a0\u2026, 2021 - frontiersin.org", "snippet": "\u2026 At the same time, the capabilities of existing deep learning algorithms with regard to 2D \nimage classifications are remarkable and became only available through the reduction in \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1004299452648206181&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ZS83-wf97w0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1004299452648206181&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A novel deep learning method to identify single tree species in UAV-based hyperspectral images", "title_link": "https://www.mdpi.com/695268", "publication_info": "GT Miyoshi, MS Arruda, LP Osco, J Marcato Junior\u2026\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "\u2026 In this paper, we propose a novel deep learning approach for hyperspectral imagery to \nidentify single-tree species in highly-dense areas. We evaluated images with 25 spectral bands \u2026", "cited_by": "https://scholar.google.com/scholar?cites=12928207274035479030&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:9oGB5wQ4arMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12928207274035479030&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Audio-based Bird Species Identification with Deep Convolutional Neural Networks.", "title_link": "http://ceur-ws.org/Vol-2125/paper_140.pdf?ref=https://githubhelp.com", "publication_info": "M Lasseck\u00a0- CLEF (working notes), 2018 - ceur-ws.org", "snippet": "\u2026 This paper presents deep learning techniques for audio-\u2026 to be particularly useful for biodiversity \nmonitoring and education. It \u2026 With the rise of deep learning, since 2016, the best systems \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10467799209182933958&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:xrN2g-sXRZEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10467799209182933958&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Using a deep convolutional neural network for extracting morphological traits from herbarium images", "title_link": "https://hal.archives-ouvertes.fr/hal-03500379/document", "publication_info": "Y Zhu, T Durand, E Chenin, M Pignal\u2026\u00a0- Biodiversity\u00a0\u2026, 2017 - hal.archives-ouvertes.fr", "snippet": "\u2026 We aim to use deep learning to provide a visual representation of words used to describe \nplants (eg simple, or compound leaf), and to associate those words with specimens in the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17843738601778521004&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:rCPv17exofcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17843738601778521004&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Earth Sciences", "title_link": "https://www.preprints.org/subject/browse/earth_sciences?filter=most_downloaded", "publication_info": "R On, D Learning\u00a0- Sat, 2019 - preprints.org", "snippet": "\u2026 Subject: Earth Sciences, Geology Keywords: High-spatial-resolution images; Geology; \nDeep learning; Remote sensing \u2026 Small Satellite Cloud Detection Based On Deep\u00a0\u2026", "cited_by": "https://scholar.google.com/scholar?q=related:e4bm-tPDtG8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=8049273749232846459&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8049273749232846459&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] DEEP LEARNING FOR ENVIRONMENTAL SENSING TOWARD SOCIAL WILDLIFE DATABASE", "title_link": "https://www.researchgate.net/profile/Felix-Michaud-2/publication/339211137_DEEP_LEARNING_FOR_ENVIRONMENTAL_SENSING_TOWARD_SOCIAL_WILDLIFE_DATABASE/links/5e442b1da6fdccd9659f91fb/DEEP-LEARNING-FOR-ENVIRONMENTAL-SENSING-TOWARD-SOCIAL-WILDLIFE-DATABASE.pdf", "publication_info": "C Duhart, S Russell, F Michaud, G Dublon, B Mayton\u2026 - researchgate.net", "snippet": "\u2026 We have presented an ongoing effort to deploy Deep Learning tools for automatic wildlife \nsurveying Our work shows how Deep Learning can advance significant opportunities for \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:34iyHOzlRPUJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=17673503639965173983&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17673503639965173983&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Audio based bird species identification using deep learning techniques", "title_link": "https://infoscience.epfl.ch/record/229232/files/16090547.pdf", "publication_info": "E Sprengel, M Jaggi, Y Kilcher, T Hofmann - 2016 - infoscience.epfl.ch", "snippet": "\u2026 Large scale, accurate bird recognition is essential for avian biodiversity conservation. It \nhelps us quantify the impact of land use and land management on bird species and is \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5547300416462561345&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=T3hAyLkAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=5547300416462561345&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] LifeCLEF 2021 teaser: Biodiversity Identification and Prediction Challenges", "title_link": "https://www.researchgate.net/profile/Henning-Mueller-3/publication/348394323_LifeCLEF_2021_teaser_Biodiversity_Identification_and_Prediction_Challenges/links/5ffcb56d299bf140888c6f50/LifeCLEF-2021-teaser-Biodiversity-Identification-and-Prediction-Challenges.pdf", "publication_info": "WP Vellinga, P Bonnet, I Eggel, H M\u00fcller - researchgate.net", "snippet": "\u2026 for this competition and point counts to assess biodiversity from this particular location in South \n\u2026 In the past few years, deep learning approaches have transformed the field of automated \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:un82qLpQeswJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/citations?user=UEZ9RlUAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Using deep learning to protect the diversity of the ecological environment Based on the prevention and control of alien species", "title_link": "https://iopscience.iop.org/article/10.1088/1755-1315/781/5/052007/meta", "publication_info": "H Han\u00a0- IOP Conference Series: Earth and Environmental\u00a0\u2026, 2021 - iopscience.iop.org", "snippet": "\u2026 environmental degradation, and biodiversity reduction, which in turn endangers one's own \nhealth and sustainable development. [10] The sharp decline in biodiversity has become an \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:LDlBsaGm40oJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=5396339991913773356&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5396339991913773356&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Review on crop prediction using deep learning techniques", "title_link": "https://iopscience.iop.org/article/10.1088/1742-6596/1767/1/012026/meta", "publication_info": "MK Dharani, R Thamilselvan, P Natesan\u2026\u00a0- Journal of Physics\u00a0\u2026, 2021 - iopscience.iop.org", "snippet": "\u2026 The structure of the deep learning mainly termed as neural network which is processed with \n\u2026 on the biodiversity. The part of agriculture has a highest role in maintaining the biodiversity. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2730396477172441210&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:emDXNSFR5CUJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2730396477172441210&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning on underwater marine object detection: A survey", "title_link": "https://link.springer.com/chapter/10.1007/978-3-319-70353-4_13", "publication_info": "M Moniruzzaman, SMS Islam, M Bennamoun\u2026\u00a0- \u2026\u00a0on Advanced Concepts\u00a0\u2026, 2017 - Springer", "snippet": "\u2026 Deep learning, also known as deep machine learning or \u2026 This paper systematically \ndescribes the use of deep learning \u2026 , and the features and deep learning architectures used are \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15312204871759427541&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:1fc5DTThf9QJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15312204871759427541&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning-based tree classification using mobile LiDAR data", "title_link": "https://www.tandfonline.com/doi/abs/10.1080/2150704X.2015.1088668", "publication_info": "H Guan, Y Yu, Z Ji, J Li, Q Zhang\u00a0- Remote Sensing Letters, 2015 - Taylor & Francis", "snippet": "\u2026 In this letter, we propose a tree classification method, which applies a deep learning \u2026 \nBased on waveform representation, deep learning using deep Boltzmann machines (DBMs) \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17112881199731360678&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:psNygcgqfe0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17112881199731360678&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] From chemoinformatics to deep learning: an open road to drug discovery", "title_link": "https://www.future-science.com/doi/full/10.4155/fmc-2018-0449", "publication_info": "LLG Ferreira, AD Andricopulo\u00a0- Future Medicinal Chemistry, 2019 - Future Science", "snippet": "\u2026 The evolution of the ANNs has culminated in the development of deep learning (DL) systems, \nso named to contrast them with the conventional shallow networks. Performing better than \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9654599394456362131&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:k9xFO_8G_IUJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9654599394456362131&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[BOOK][B] Automated High-Throughput Organismal Image Segmentation Using Deep Learning for Massive Phenotypic Analysis", "title_link": "https://search.proquest.com/openview/2a5eebaf61523ee45e153ced8472a525/1?pq-origsite=gscholar&cbl=18750&diss=y", "publication_info": "ST Schwartz - 2021 - search.proquest.com", "snippet": "\u2026 biodiversity from image databases. Image segmentation meta- algorithms using deep \nlearning \u2026 (CNNs) have been trained on a small fraction of biodiversity, thus limiting their utility. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7606874635122994751&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:P25vfS0MkWkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7606874635122994751&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "The Flora Incognita app\u2013interactive plant species identification", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13611", "publication_info": "P M\u00e4der, D Boho, M Rzanny, M Seeland\u2026\u00a0- Methods in Ecology\u00a0\u2026, 2021 - Wiley Online Library", "snippet": "\u2026 Specifically developed deep learning algorithms, trained on an extensive repository of plant \n\u2026 data exchange with biodiversity platforms like the Global Biodiversity Information Facility (\u2026", "cited_by": "https://scholar.google.com/scholar?cites=9896255724434341243&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=8r5t0FMAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=9896255724434341243&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "U-Infuse: Democratization of Customizable Deep Learning for Object Detection", "title_link": "https://www.mdpi.com/1064374", "publication_info": "A Shepley, G Falzon, C Lawson, P Meek, P Kwan\u00a0- Sensors, 2021 - mdpi.com", "snippet": "\u2026 data used in biodiversity conservation and management \u2026 Deep learning models have \nbeen used to achieve this task \u2026 need to democratize access to deep learning technologies by \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:DjURbeEU2igJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=2943688264870081806&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2943688264870081806&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Landslide detection of hyperspectral remote sensing data based on deep learning with constrains", "title_link": "https://ieeexplore.ieee.org/abstract/document/8911205/", "publication_info": "C Ye, Y Li, P Cui, L Liang, S Pirasteh\u2026\u00a0- IEEE Journal of\u00a0\u2026, 2019 - ieeexplore.ieee.org", "snippet": "\u2026 deep learning-based methods for landslide detection on hyperspectral images. We proposes \na deep learning \u2026 heterogeneous forest biodiversity assessment,\u201d Int. J. Remote Sens., vol. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13901080237254303453&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:3d6-H9OO6sAJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13901080237254303453&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Ensemble of deep learning-based multimodal remote sensing image classification model on unmanned aerial vehicle networks", "title_link": "https://www.mdpi.com/1370426", "publication_info": "GP Joshi, F Alenezi, G Thirumoorthy, AK Dutta, J You\u00a0- Mathematics, 2021 - mdpi.com", "snippet": "\u2026 Detrimental modifications in land-use and land-cover (LULC) are the primary contributor \nto dramatic climate changes, terrestrial biodiversity losses, and harms to the ecosystem [2]. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2062069997004416376&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:eGVwqbzxnRwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2062069997004416376&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Seed Dispenser using Drones and Deep Learning Techniques for Reforestation", "title_link": "https://ieeexplore.ieee.org/abstract/document/9418227/", "publication_info": "GVS Lohit, D Bisht\u00a0- 2021 5th International Conference on\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 The main and primary reason for this, is continuing to be the agricultural expansion and \ncommercial production, which leads to loss of forest biodiversity. Almost 40 percent of the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10203096387037476148&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:NLVwDhuumI0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Plant Identification: Experts vs. Machines in the Era of Deep Learning", "title_link": "https://books.google.com/books?hl=en&lr=&id=4upgDwAAQBAJ&oi=fnd&pg=PA131&dq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&ots=U8vnpUDIaz&sig=7-weVqxDKlb1LVaPWkNfP2LJHaI", "publication_info": "DLTCF Experts\u00a0- \u2026\u00a0Applications for Environmental & Biodiversity\u00a0\u2026, 2018 - books.google.com", "snippet": "Automated identification of plants and animals have improved considerably in the last few \nyears, in particular thanks to the recent advances in deep learning. The next big question is \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:0hCw65bzQ0AJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[PDF][PDF] Counting Sea Lions from Aerial Photography using Deep Learning with Density Maps", "title_link": "https://drive.google.com/file/d/1KKAyoKPK3XT-bGt1nap7Kn1_JiymuxWc/view", "publication_info": "CP PADUBIDRI, A KAMILARIS, S KARATSIOLIS\u2026 - 2018 - drive.google.com", "snippet": "\u2026 populations in relation to biodiversity and maintain balance \u2026 of computer vision, through \ndeep learning (DL) architecture, \u2026 Results We have trained two deep learning models, a basic \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:-rFRJhsvhicJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Leveraging the Benefits of Open Data Services for Natural History Collection Management", "title_link": "https://search.proquest.com/openview/34f7acdbc07cbb90b3504ec693abbd5d/1?pq-origsite=gscholar&cbl=2049297", "publication_info": "M Schermer, D Duin\u00a0- Biodiversity Information Science and\u00a0\u2026, 2018 - search.proquest.com", "snippet": "\u2026 Naturalis Biodiversity Center, home to one of the largest \u2026 To this end, we developed the \nNetherlands Biodiversity Data \u2026 use in the development of deep learning models, thematic portals (\u2026", "cited_by": "https://scholar.google.com/scholar?cluster=7630638777951278499&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=7630638777951278499&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Associations between trees and grass presence with childhood asthma prevalence using deep learning image segmentation and a novel green view index", "title_link": "https://www.sciencedirect.com/science/article/pii/S0269749121011647", "publication_info": "H Yu, Y Zhou, R Wang, Z Qian, LD Knibbs\u2026\u00a0- Environmental\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 This study showed that using street view images with a deep learning method is a promising \napproach to assess exposure to green space. With this novel method, we observed that \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7588649392717908477&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:_UnvkWpMUGkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7588649392717908477&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Extinction in the Anthropocene", "title_link": "https://www.cell.com/current-biology/pdf/S0960-9822(19)30885-1.pdf", "publication_info": "ST Turvey, JJ Crees\u00a0- Current Biology, 2019 - cell.com", "snippet": "\u2026 A survey on deep learning in medical image analysis. Med. Image Anal. \u2026 punctuated by \nbrief intervals of hugely elevated biodiversity loss caused by natural events including volcanism, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3719890214929347054&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:7rFQEHG0nzMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3719890214929347054&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Identifying animal species in camera trap images using deep learning and citizen science", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13099", "publication_info": "M Willi, RT Pitman, AW Cardoso\u2026\u00a0- Methods in Ecology\u00a0\u2026, 2019 - Wiley Online Library", "snippet": "\u2026 Advances in machine learning, especially deep learning, allow for accurate automatic \u2026 The \ngoals of this study were to (a) assess the accuracy of deep learning in classifying camera trap \u2026", "cited_by": "https://scholar.google.com/scholar?cites=18275883569063522485&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:tfBtukb7oP0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=18275883569063522485&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Hierarchical classification of very small objects: Application to the detection of arthropod species", "title_link": "https://ieeexplore.ieee.org/abstract/document/9411844/", "publication_info": "P Tresson, D Carval, P Tixier, W Puech\u00a0- IEEE Access, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 that are challenging for the use of deep learning. Classes are often imbalanced, similar, \u2026 \nbiodiversity. This dataset shows several constraints that are frequent when using deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16775649959027467043&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=es0QRS4AAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=16775649959027467043&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Mosquito detection with neural networks: the buzz of deep learning", "title_link": "https://arxiv.org/abs/1705.05180", "publication_info": "I Kiskin, BP Orozco, T Windebank, D Zilli\u2026\u00a0- arXiv preprint arXiv\u00a0\u2026, 2017 - arxiv.org", "snippet": "\u2026 deep learning architectures trained on large data sets. This paper presents an application of \ndeep learning \u2026 Sound can therefore be used to locate individuals for biodiversity monitoring, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17356704119148255823&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:TxpkxW9m3_AJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17356704119148255823&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Mosquito Detection using Deep Learning based on Acoustics", "title_link": "https://www.cibgp.com/article_7902_40a87cb2089e870a7aefb278fa2ad2f5.pdf", "publication_info": "AS Bist, M Mursleen, L Mohan, H Pant\u2026\u00a0- Journal of Contemporary\u00a0\u2026, 2021 - cibgp.com", "snippet": "\u2026 proposing a deep learning based pipeline \u2026 Deep learning for detection of bird vocalisations \n[8] Authors used deep auto-encoders for identifying bird activity that will lead to biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:jPpZmr2Tn44J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=10277095317230451340&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10277095317230451340&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automatic acoustic detection of birds through deep learning: the first bird audio detection challenge", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13103", "publication_info": "D Stowell, MD Wood, H Pamu\u0142a\u2026\u00a0- Methods in Ecology\u00a0\u2026, 2019 - Wiley Online Library", "snippet": "\u2026 power but also due to deep learning methods that can learn \u2026 its outcomes, with new deep \nlearning methods able to achieve \u2026 art represented by the deep learning methods that excelled \u2026", "cited_by": "https://scholar.google.com/scholar?cites=50270686932665232&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:kIM8ZeyYsgAJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=50270686932665232&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for fine-grained image analysis: A survey", "title_link": "https://arxiv.org/abs/1907.03069", "publication_info": "XS Wei, J Wu, Q Cui\u00a0- arXiv preprint arXiv:1907.03069, 2019 - arxiv.org", "snippet": "\u2026 deep learning, recent years have witnessed remarkable progress of FGIA using deep learning \n\u2026 In this paper, we aim to give a survey on recent advances of deep learning based FGIA \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3987780767402723988&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:lIos03pxVzcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3987780767402723988&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automated bird counting with deep learning for regional bird distribution mapping", "title_link": "https://www.mdpi.com/770228", "publication_info": "HG Ak\u00e7ay, B Kabasakal, D Aksu, N Demir, M \u00d6z\u2026\u00a0- Animals, 2020 - mdpi.com", "snippet": "\u2026 are good indicators of habitat quality and biodiversity [4,5,6,7]. However, recent studies \nindicate that likewise the most of the global biodiversity components, birds are declining in the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13471720154428475843&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=1_yfwhEAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=13471720154428475843&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for land use and land cover classification based on hyperspectral and multispectral earth observation data: A review", "title_link": "https://www.mdpi.com/788092", "publication_info": "A Vali, S Comai, M Matteucci\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "\u2026 are the leading contributors to terrestrial biodiversity losses [2], \u2026 In the last decade, Deep \nLearning algorithms have shown \u2026 However, despite the massive success of deep learning in \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4126890639917523759&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:LyMr-yupRTkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4126890639917523759&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Semantic Retrieval of Microbiome Information Based on Deep Learning", "title_link": "https://link.springer.com/chapter/10.1007/978-981-33-6987-0_4", "publication_info": "J Alphonse, AN Binosh, S Raj, S Pal\u2026\u00a0- Advances in Computing\u00a0\u2026, 2021 - Springer", "snippet": "\u2026 Developing a fundamental understanding of the biodiversity of sewage microbiome or finding \nout the key species that can be targeted to significantly reduce the pathogenic population \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:lgZQGC6fJ3YJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=8513948640892421782&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8513948640892421782&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Prototyping Artificial Intelligent Classifiers using Deep Learning", "title_link": "https://www.authorea.com/doi/full/10.22541/au.159493450.09431478", "publication_info": "HN Chege\u00a0- Authorea Preprints, 2020 - authorea.com", "snippet": "\u2026 Point 1: Deep learning algorithms are revolutionizing how \u2026 subfields, the use of deep learning \nis slowly but steadily increasing. \u2026 the general workflow of a deep learning pipeline meant to \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6813188200394440701&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:_b9kCJJOjV4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6813188200394440701&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Ecological evolution path of smart education platform based on deep learning and image detection", "title_link": "https://www.sciencedirect.com/science/article/pii/S0141933120305020", "publication_info": "Z Han, A Xu\u00a0- Microprocessors and Microsystems, 2021 - Elsevier", "snippet": "\u2026 Ecological columns are usually lined with biological species such as biodiversity, various \nstrips of natural elements, protecting the migration of animal habitat, preventing sandstorms, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7000234222160375294&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:_u1mrO_TJWEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community", "title_link": "https://www.spiedigitallibrary.org/journals/Journal-of-Applied-Remote-Sensing/volume-11/issue-4/042609/Comprehensive-survey-of-deep-learning-in-remote-sensing--theories/10.1117/1.JRS.11.042609.short", "publication_info": "JE Ball, DT Anderson\u2026\u00a0- Journal of applied remote\u00a0\u2026, 2017 - spiedigitallibrary.org", "snippet": "\u2026 assess biodiversity modeling. Biodiversity occurs at all levels from molecular to individual \nanimals, to ecosystem, and to global. This requires a large variety of sensors and analysis at \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7702196985800562138&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:2hW6wFmz42oJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7702196985800562138&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep learning-based appearance features extraction for automated carp species identification", "title_link": "https://www.sciencedirect.com/science/article/pii/S0144860919302195", "publication_info": "A Banan, A Nasiri, A Taheri-Garavand\u00a0- Aquacultural Engineering, 2020 - Elsevier", "snippet": "\u2026 Hence, in this study, a deep learning neural network as a smart, real-time and non-destructive \nmethod was developed and applied to automate the identification of four economically \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7608590179221884719&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:L88LunQkl2kJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7608590179221884719&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Proceedings of the 10th International Conference on Ecological Informatics: translating ecological data into knowledge and decisions in a rapidly changing world: ICEI\u00a0\u2026", "title_link": "https://www.db-thueringen.de/receive/dbt_mods_00038375", "publication_info": "J Gaikwad, B K\u00f6nig-Ries\u2026\u00a0- ICEI 2018: 10th\u00a0\u2026, 2018 - db-thueringen.de", "snippet": "\u2026 by deep learning, \u2022 advanced exploration of valuable information in \u2018big data\u2019 by means \nof machine learning and process modelling, \u2022 decision-informing solutions for biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=9164224599905259685&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=9164224599905259685&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Global observational needs and resources for marine biodiversity", "title_link": "https://www.frontiersin.org/articles/10.3389/fmars.2019.00367/full", "publication_info": "G Canonico, PL Buttigieg, E Montes\u2026\u00a0- Frontiers in Marine\u00a0\u2026, 2019 - frontiersin.org", "snippet": "\u2026 Deep learning techniques enable automated classification of species from a variety of \u2026 \nUsing this technology, sensor platforms could stream data into Deep Learning classifiers that \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5023508557459495757&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:TRuC1WoWt0UJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5023508557459495757&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Monitoring ecosystem service change in the City of Shenzhen by the use of high\u2010resolution remotely sensed imagery and deep learning", "title_link": "https://onlinelibrary.wiley.com/doi/abs/10.1002/ldr.3337", "publication_info": "X Huang, X Han, S Ma, T Lin\u2026\u00a0- Land Degradation &\u00a0\u2026, 2019 - Wiley Online Library", "snippet": "\u2026 In particular, deep learning was used to obtain accurate land\u2010use maps, because this \ntechnique is able to model the hierarchical representations of features and can thus effectively \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14693033106135343622&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:BmJAVMMj6MsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14693033106135343622&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Examining the spatial distribution and temporal change of the green view index in New York City using Google Street View images and deep learning", "title_link": "https://journals.sagepub.com/doi/abs/10.1177/2399808320962511", "publication_info": "X Li\u00a0- Environment and Planning B: Urban Analytics and City\u00a0\u2026, 2021 - journals.sagepub.com", "snippet": "\u2026 This study applied deep learning and computer vision algorithms on the historical GSV \nimages collected over the last 10 years to examine the temporal change of street tree canopies in \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10731743027788479139&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:o3obsGzP7pQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10731743027788479139&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] ResNeXt convolution neural network topology-based deep learning model for identification and classification of Pediastrum", "title_link": "https://www.sciencedirect.com/science/article/pii/S221192642030312X", "publication_info": "G Pant, DP Yadav, A Gaur\u00a0- Algal research, 2020 - Elsevier", "snippet": "\u2026 Although deep learning-based studies for identification and classification of Pediastrum \u2026 \n, and Stauridium tetras with the help of deep learning - modified ResNeXt CNN model. The \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14746582707269605078&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:1ha5bddipswJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14746582707269605078&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Classification and Detection of Plant Leaf Diseases Using Various Deep Learning Techniques and Convolutional Neural Network", "title_link": "https://link.springer.com/chapter/10.1007/978-3-030-93247-3_14", "publication_info": "PP Mazumder, M Hossain, MH Riaz\u00a0- International Conference on\u00a0\u2026, 2021 - Springer", "snippet": "\u2026 a Convolutional Neural Network model for detecting and classifying simple leaves images \nof (mostly) diseased plants and healthy plants with the help of different types of deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:ClIPTrAFq6QJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "LifeCLEF 2019: biodiversity identification and prediction challenges", "title_link": "https://link.springer.com/chapter/10.1007/978-3-030-15719-7_37", "publication_info": "A Joly, H Go\u00ebau, C Botella, S Kahl, M Poupard\u2026\u00a0- \u2026\u00a0on Information Retrieval, 2019 - Springer", "snippet": "\u2026 deficient regions, ie regions having the richest biodiversity (tropical ones) but for which data \n\u2026 We actually did show in previous editions of LifeCLEF that training deep learning models on \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2607530132254092669&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=o2blBQQAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=2607530132254092669&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Seasonal Arctic sea ice forecasting with probabilistic deep learning", "title_link": "https://www.nature.com/articles/s41467-021-25257-4?tpcc=nleyeonai", "publication_info": "TR Andersson, JS Hosking, M P\u00e9rez-Ortiz\u2026\u00a0- Nature\u00a0\u2026, 2021 - nature.com", "snippet": "\u2026 We present a probabilistic, deep learning sea ice forecasting system, IceNet. The system \nhas been trained on climate simulations and observational data to forecast the next 6 months of \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1651633591133053183&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:_6CWGgDI6xYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1651633591133053183&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep-learning Versus OBIA for Scattered Shrub Detection with Google Earth Imagery: Ziziphus lotus as Case Study", "title_link": "http://repositorio.ual.es/handle/10835/7401", "publication_info": "E Guirado Hern\u00e1ndez, S Tabik, D Alcaraz Segura\u2026 - 2017 - repositorio.ual.es", "snippet": "\u2026 , eg, in land-use planning and biodiversity conservation. Developing such maps has been \n\u2026 Recently, deep learning Convolutional Neural Networks (CNNs) have shown outstanding \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:w2UmuNSpzKMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[HTML][HTML] Explainable identification and mapping of trees using UAV RGB image and deep learning", "title_link": "https://www.nature.com/articles/s41598-020-79653-9", "publication_info": "M Onishi, T Ise\u00a0- Scientific reports, 2021 - nature.com", "snippet": "\u2026 For interpreting the deep learning classification, algorithms which visualize some features of \n\u2026 features that deep learning used, which means we can know whether deep learning really \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6834896711539765621&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:dTHQp1hu2l4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6834896711539765621&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[CITATION][C] Wringing out moisture from deep learning: high-res (250m) soil moisture predictions across the Western USA to estimate tree seedling survival and forest\u00a0\u2026", "title_link": "https://ui.adsabs.harvard.edu/abs/2020AGUFMB060.0025C/abstract", "publication_info": "L Calle, MP Maneta, Z Holden\u2026\u00a0- AGU Fall Meeting\u00a0\u2026, 2020 - ui.adsabs.harvard.edu", "snippet": "Wringing out moisture from deep learning: high-res (250m) soil moisture predictions across \nthe Western USA to estimate tree seedling survival and forest regeneration. - NASA/ADS \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=2892126418916085346&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=2892126418916085346&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automated conservation assessment of the orchid family using deep learning", "title_link": "https://www.biorxiv.org/content/10.1101/2020.06.11.145557.abstract", "publication_info": "A Zizka, D Silvestro, P Vitt, TM Knight\u00a0- bioRxiv, 2020 - biorxiv.org", "snippet": "IUCN Red List assessments are essential for prioritizing conservation needs but are \nresource-intensive and therefore only available for a fraction of global species richness. Tropical \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:UKeof1vAbU8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/citations?user=QMqWqrkAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=5723442200674084688&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Characterization of food cultivation along roadside transects with Google Street View imagery and deep learning", "title_link": "https://www.sciencedirect.com/science/article/pii/S016816991831144X", "publication_info": "J Ringland, M Bohm, SR Baek\u00a0- Computers and electronics in agriculture, 2019 - Elsevier", "snippet": "\u2026 , 2018) reviewed 40 applications of deep learning to problems in agriculture: the authors \nargue that the image classification results using deep learning in these applications to be very \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1156152993641924977&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:cQkIrAV7CxAJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1156152993641924977&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "BettaNet: A Deep Learning Architecture for Classification of Wild Siamese Betta Species", "title_link": "https://iopscience.iop.org/article/10.1088/1757-899X/1055/1/012104/meta", "publication_info": "V Pattana-Anake, P Danphitsanuparn\u2026\u00a0- IOP Conference Series\u00a0\u2026, 2021 - iopscience.iop.org", "snippet": "\u2026 Deep Learning methods have been gaining popularity in many biological domains. Fish \nclassification also uses deep learning. Especially for the surveillance of underwater fish species \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4379965840281373807&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:bwxRxrnDyDwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4379965840281373807&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Combining machine learning & reasoning for biodiversity data intelligence", "title_link": "https://ojs.aaai.org/index.php/AAAI/article/view/17750", "publication_info": "A Sen, B Sterner, N Franz, C Powel\u2026\u00a0- Proceedings of the AAAI\u00a0\u2026, 2021 - ojs.aaai.org", "snippet": "\u2026 Our approach is also novel from the perspective of ontology alignment, by combining a \ndeep learning method for classifying individual data records, with automated reasoning, in a \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7990924266683379459&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=I9rpaiwAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=7990924266683379459&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Tree extraction of airborne lidar data based on coordinates of deep learning object detection from orthophoto over complex mangrove forest", "title_link": "https://www.academia.edu/download/63701064/ijeter103852020-220200621-14235-n9rq21.pdf", "publication_info": "AS Alon, ED Festijo, CD Casuat\u00a0- International Journal, 2020 - academia.edu", "snippet": "\u2026 and predict growth and yield, or also to classify trees with strong biodiversity values [2]. \u2026 \nspecific tree genus, in particular, a deep learning technique for tree identification was used, using \u2026", "cited_by": "https://scholar.google.com/scholar?cites=345740326634114301&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:_cyNyf5QzAQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=345740326634114301&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Smart insect cameras", "title_link": "https://biss.pensoft.net/article/39241/download/pdf/", "publication_info": "L Hogeweg, T Zeegers, I Katramados\u2026\u00a0- Biodiversity Information\u00a0\u2026, 2019 - biss.pensoft.net", "snippet": "\u2026 The cameras are made smart with image processing, consisting of image enhancement, \ninsect detection and species identification being performed, using deep learning based \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14543138561915456266&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:CotBHnib08kJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14543138561915456266&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Effects of sample size and network depth on a deep learning approach to species distribution modeling", "title_link": "https://www.sciencedirect.com/science/article/pii/S157495412030087X", "publication_info": "DJ Benkendorf, CP Hawkins\u00a0- Ecological Informatics, 2020 - Elsevier", "snippet": "\u2026 Such empirical studies are critical to determining if deep learning is a viable option for a \u2026 \nHowever, to our knowledge, deep learning has not been applied to macroinvertebrate \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13975879458004452217&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ecMI1lFM9MEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13975879458004452217&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Shazam for bats: Internet of Things for continuous real\u2010time biodiversity monitoring", "title_link": "https://ietresearch.onlinelibrary.wiley.com/doi/abs/10.1049/smc2.12016", "publication_info": "S Gallacher, D Wilson, A Fairbrass\u2026\u00a0- IET Smart\u00a0\u2026, 2021 - Wiley Online Library", "snippet": "\u2026 As such, we can then utilise deep learning modes typically used in computer vision, called \nConvolutional Neural Networks (CNNs), to process the image and classify patterns that \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10577026246548077887&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Pz177VQlyZIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10577026246548077887&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A combination of transfer learning and deep learning for medicinal plant classification", "title_link": "https://dl.acm.org/doi/abs/10.1145/3321454.3321464", "publication_info": "N Duong-Trung, LD Quach, MH Nguyen\u2026\u00a0- Proceedings of the 2019\u00a0\u2026, 2019 - dl.acm.org", "snippet": "\u2026 With its abundant indigenous plant varieties, medicinal plants, and associated traditional \nknowledge, it is undoubtedly that Viet Nam\u2019s biodiversity has a crucial role in contributing to \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5453430268337420202&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:qnedf-95rksJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Improving acoustic monitoring of biodiversity using deep learning-based source separation algorithms", "title_link": "https://www.db-thueringen.de/receive/dbt_mods_00037825", "publication_info": "MN Tuanmu, TH Lin, J Huang, Y Tsao\u2026\u00a0- ICEI 2018: 10th\u00a0\u2026, 2018 - db-thueringen.de", "snippet": "Passive acoustic monitoring of the environment has been suggested as an effective tool for \ninvestigating the dynamics of biodiversity across spatial and temporal scales. Recent \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=8947171811091725450&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/citations?user=ZO5e5I4AAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=8947171811091725450&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Combining Sentinel-1 and Sentinel-2 Satellite Image Time Series for land cover mapping via a multi-source deep learning architecture", "title_link": "https://www.sciencedirect.com/science/article/pii/S0924271619302278", "publication_info": "D Ienco, R Interdonato, R Gaetano\u2026\u00a0- ISPRS Journal of\u00a0\u2026, 2019 - Elsevier", "snippet": "\u2026 In this work, we propose a deep learning architecture to combine information coming from \nS1 and S2 time series, namely TWINNS (TWIn Neural Networks for Sentinel data), able to \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15233210788747071411&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:s8_q24A8Z9MJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15233210788747071411&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Estimating Gross Primary Productivity in Crops with Satellite Data, Radiative Transfer Modeling and Machine Learning", "title_link": "https://gfzpublic.gfz-potsdam.de/rest/items/item_4950899_1/component/file_4950898/content", "publication_info": "A Wolanin, L Guanter\u2026\u00a0- 10th International\u00a0\u2026, 2018 - gfzpublic.gfz-potsdam.de", "snippet": "\u2026 by deep learning,\u2022 advanced exploration of valuable information in \u2018big data\u2019by means of \nmachine learning and process modelling,\u2022 decision-informing solutions for biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cluster=3524153235111266442&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.com/scholar?cluster=3524153235111266442&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Efficient, automated and robust pollen analysis using deep learning", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13575", "publication_info": "O Olsson, M Karlsson, AS Persson\u2026\u00a0- Methods in Ecology\u00a0\u2026, 2021 - Wiley Online Library", "snippet": "\u2026 We present an automated method for pollen analysis, based on deep learning convolutional \nneural networks (CNN). We scanned microscope slides with fuchsine stained, fresh pollen \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11778273807947294614&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:lmf81Z_VdKMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11778273807947294614&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Exploring the octanol\u2013water partition coefficient dataset using deep learning techniques and data augmentation", "title_link": "https://www.nature.com/articles/s42004-021-00528-9", "publication_info": "N Ulrich, KU Goss, A Ebert\u00a0- Communications Chemistry, 2021 - nature.com", "snippet": "\u2026 deal with the analysis of big datasets and develop deep learning models, often only have \na \u2026 are rarely specialists in deep learning. Novel deep learning libraries like DeepChem 16,17 \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10498105047158876139&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:6-ejRuvCsJEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10498105047158876139&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Visualizing abnormalities in chest radiographs through salient network activations in deep learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/8268146/", "publication_info": "R Sivaramakrishnan, S Antani, Z Xue\u2026\u00a0- 2017 IEEE life\u00a0\u2026, 2017 - ieeexplore.ieee.org", "snippet": "\u2026 To overcome challenges of devising highperforming hand-crafted features that capture the \nvariance in the underlying data, Deep Learning (DL), also known as hierarchical machine \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8104313663427975580&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:nBn4oFZOeHAJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8104313663427975580&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Fish detection and species classification in underwater environments using deep learning with temporal information", "title_link": "https://www.sciencedirect.com/science/article/pii/S1574954120300388", "publication_info": "A Jalal, A Salman, A Mian, M Shortis, F Shafait\u00a0- Ecological Informatics, 2020 - Elsevier", "snippet": "\u2026 This region is home to the largest fish biodiversity environments in the world with over 3000 \ndifferent fish species. The second dataset is collected by our research group in the University \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15051996222126555096&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=K8W4ywcAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=15051996222126555096&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Habitat-Net: Segmentation of habitat images using deep learning", "title_link": "https://www.sciencedirect.com/science/article/pii/S1574954118302759", "publication_info": "JF Abrams, A Vashishtha, ST Wong, A Nguyen\u2026\u00a0- Ecological\u00a0\u2026, 2019 - Elsevier", "snippet": "\u2026 To shorten the time to process the data we propose here Habitat-Net: a novel deep learning \napplication based on Convolutional Neural Networks (CNN) to segment habitat images of \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16789768854094664265&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:SdI6GdE9AekJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16789768854094664265&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep learning identification for citizen science surveillance of tiger mosquitoes", "title_link": "https://www.nature.com/articles/s41598-021-83657-4", "publication_info": "BA Pataki, J Garriga, R Eritja, JRB Palmer\u2026\u00a0- Scientific reports, 2021 - nature.com", "snippet": "\u2026 , from the life sciences, where they help assess biodiversity at a global scale (eg iNaturalist, \n\u2026 , powering a big data approach to biodiversity quantification and worldwide conservation. In \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13780261518306870331&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:O4SqBtdSPb8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13780261518306870331&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A study on the detection of cattle in UAV images using deep learning", "title_link": "https://www.mdpi.com/592188", "publication_info": "JGA Barbedo, LV Koenigkan, TT Santos, PM Santos\u00a0- Sensors, 2019 - mdpi.com", "snippet": "\u2026 This article presented a study on the use of deep learning models for the detection of cattle \n(Canchim breed) in UAV images. The experiments were designed to test the robustness of 15 \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6012609586256165962&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=3OHMrdUAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=6012609586256165962&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Nanomaterials for targeted delivery of agrochemicals by an all-in-one combination strategy and deep learning", "title_link": "https://pubs.acs.org/doi/abs/10.1021/acsami.1c11914", "publication_info": "Y Ji, S Ma, S Lv, Y Wang, S Lu\u2026\u00a0- ACS Applied Materials &\u00a0\u2026, 2021 - ACS Publications", "snippet": "\u2026 In summary, efforts are dedicated to combining the PFAC strategy and deep learning, to \u2026 \nBy introducing object detection based on deep learning, targeted weeding was achieved. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9546741100197234646&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:1sfgJ3PWfIQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9546741100197234646&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Projecting Australia's forest cover dynamics and exploring influential factors using deep learning", "title_link": "https://www.sciencedirect.com/science/article/pii/S1364815218304237", "publication_info": "L Ye, L Gao, R Marcos-Martinez, D Mallants\u2026\u00a0- \u2026\u00a0Modelling & Software, 2019 - Elsevier", "snippet": "\u2026 This study presents the first application of deep learning \u2026 -Term Memory (LSTM) deep learning \nneural networks applied to a \u2026 Deep learning greatly outperformed a state-of-the-art spatial-\u2026", "cited_by": "https://scholar.google.com/scholar?cites=14629076538270774255&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:73Ohd5rrBMsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14629076538270774255&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "The history and impact of digitization and digital data mobilization on biodiversity research", "title_link": "https://royalsocietypublishing.org/doi/abs/10.1098/rstb.2017.0391", "publication_info": "G Nelson, S Ellis\u00a0- \u2026\u00a0Transactions of the Royal Society B, 2019 - royalsocietypublishing.org", "snippet": "\u2026 and species distribution modelling [54]; the use of 3D data for generating and testing new \nhypotheses; the implementation of convolutional neural networks (CNN) and deep learning in \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7842717563821282639&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:T9VIYRLu1mwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7842717563821282639&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Plant leaves classification: A few-shot learning method based on siamese network", "title_link": "https://ieeexplore.ieee.org/abstract/document/8869770/", "publication_info": "B Wang, D Wang\u00a0- IEEE Access, 2019 - ieeexplore.ieee.org", "snippet": "\u2026 Therefore, it is particularly important to protect the biodiversity \u2026 However, the disadvantages \nof deep learning are also obvi\u2026 samples, and general deep learning neural networks perform \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11110810810461592173&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:bRoihJCHMZoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11110810810461592173&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A transdisciplinary review of deep learning research and its relevance for water resources scientists", "title_link": "https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018WR022643", "publication_info": "C Shen\u00a0- Water Resources Research, 2018 - Wiley Online Library", "snippet": "Deep learning (DL), a new generation of artificial neural network research, has transformed \nindustries, daily lives, and various scientific disciplines in recent years. DL represents \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9509669822736972506&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:2jp9w1Ei-YMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9509669822736972506&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Cephalopod species identification using integrated analysis of machine learning and deep learning approaches", "title_link": "https://peerj.com/articles/11825/", "publication_info": "HY Tan, ZY Goh, KH Loh, AYH Then, H Omar\u2026\u00a0- PeerJ, 2021 - peerj.com", "snippet": "\u2026 of morphometric, machine learning and deep learning approaches. Eight machine learning \n\u2026 Malaysia which is important for documentation of the country\u2019s rich marine biodiversity. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13848245583064298364&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:fHPrlPzZLsAJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13848245583064298364&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Medical Image Retrieval System Using Deep Learning Techniques", "title_link": "https://link.springer.com/chapter/10.1007/978-3-030-71676-9_5", "publication_info": "J Pradhan, AK Pal, H Banka\u00a0- Deep Learning for Biomedical Data\u00a0\u2026, 2021 - Springer", "snippet": "\u2026 , crime prevention, hyper-spectral imaging, biodiversity information system, fingerprint \nidentification, etc. Further, different deep learning models and their application on medical image \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:F_OV_e2o3VsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=6619632767419675415&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6619632767419675415&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep image representations for coral image classification", "title_link": "https://ieeexplore.ieee.org/abstract/document/8255621/", "publication_info": "A Mahmood, M Bennamoun, S An\u2026\u00a0- IEEE Journal of\u00a0\u2026, 2018 - ieeexplore.ieee.org", "snippet": "\u2026 This has resulted in a dramatic decline in our planet\u2019s marine biodiversity [5]. To minimize \nthese negative \u2026 This paper proposes a computer vision and deep learning based framework to \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14744437588013558932&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:lCx37t3DnswJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14744437588013558932&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning in forestry using uav-acquired rgb data: A practical review", "title_link": "https://www.mdpi.com/2072-4292/13/14/2837", "publication_info": "Y Diez, S Kentsch, M Fukuda, MLL Caceres\u2026\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 In addition to this trend, deep learning (DL) has also been gaining much attention in the \nfield of forestry as a way to include the knowledge of forestry experts into automatic software \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5520588759774186774&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Fs1aSToSnUwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5520588759774186774&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Forest monitoring in guatemala using satellite imagery and deep learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/8899782/", "publication_info": "NS Wyniawskyj, M Napiorkowska\u2026\u00a0- IGARSS 2019-2019\u00a0\u2026, 2019 - ieeexplore.ieee.org", "snippet": "\u2026 estimated long-term deforestation using optical and radar satellite imagery [1, 5] however \nat the time of this paper, this is limited to time-series analysis and does not use deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8057886804396863054&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Tu5hKFtd028J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Systematic review of deep learning and machine learning models in biofuels research", "title_link": "https://link.springer.com/chapter/10.1007/978-3-030-36841-8_2", "publication_info": "S Ardabili, A Mosavi, AR V\u00e1rkonyi-K\u00f3czy\u00a0- International Conference on\u00a0\u2026, 2019 - Springer", "snippet": "\u2026 Recently, machine learning and deep learning techniques have been accessible in \nmodeling, optimizing and handling the biodiesel production, consumption, and its environmental \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11204928279408745797&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:RR3jY-fmf5sJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11204928279408745797&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Human gut microbiome aging clock based on taxonomic profiling and deep learning", "title_link": "https://www.sciencedirect.com/science/article/pii/S2589004220303849", "publication_info": "F Galkin, P Mamoshina, A Aliper, E Putin, V Moskalev\u2026\u00a0- Iscience, 2020 - Elsevier", "snippet": "\u2026 Here we developed a method of predicting hosts' age based on microflora taxonomic \nprofiles using a cross-study dataset and deep learning. Our best model has an architecture of a \u2026", "cited_by": "https://scholar.google.com/scholar?cites=741384305865160090&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=Dyj_uSMAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=741384305865160090&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Adopting deep learning methods for airborne RGB fluvial scene classification", "title_link": "https://www.sciencedirect.com/science/article/pii/S0034425720304806", "publication_info": "PE Carbonneau, SJ Dugdale, TP Breckon\u2026\u00a0- Remote Sensing of\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 to demonstrate the potential of deep learning methods to fluvial scientists and river \nmanagers. Second, we evaluate the potential of a deep learning workflow called CNN-Supervised \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4465398880900298384&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:kDZ9nJ9I-D0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4465398880900298384&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Classification of hybrid seeds using near-infrared hyperspectral imaging technology combined with deep learning", "title_link": "https://www.sciencedirect.com/science/article/pii/S0925400519308251", "publication_info": "P Nie, J Zhang, X Feng, C Yu, Y He\u00a0- Sensors and Actuators B: Chemical, 2019 - Elsevier", "snippet": "\u2026 Deep learning is a branch in the field of machine learning. In recent years, deep learning \u2026 \nDeep learning algorithms can process input data layer by layer, transform the features of the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15953582764748221893&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:xa2cs_-CZt0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15953582764748221893&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Methods, New Software Tools, and Best Practices for Developing High-quality Training Data for Machine Learning-based Image Analysis in Biodiversity Research.", "title_link": "https://go.gale.com/ps/i.do?id=GALE%7CA646493759&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=25350897&p=AONE&sw=w", "publication_info": "BJ Stucky, L Brenskelle, R Guralnick\u00a0- Biodiversity Information Science\u00a0\u2026, 2019 - go.gale.com", "snippet": "\u2026 Recent progress in using deep learning techniques to automate the analysis of \u2026 in \nbiodiversity science. However, potential applications of machine learning methods in biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8645496349048748506&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:2rn8px_5-ncJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8645496349048748506&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Machine learning for image based species identification", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13075", "publication_info": "J W\u00e4ldchen, P M\u00e4der\u00a0- Methods in Ecology and Evolution, 2018 - Wiley Online Library", "snippet": "\u2026 In this paper, we focus on deep learning neural networks as a \u2026 We review selected deep \nlearning approaches for image \u2026 Many activities, such as studying the biodiversity richness of a \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13993935335504728333&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:DdGLagtyNMIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13993935335504728333&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Going further with model verification and deep learning", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13494", "publication_info": "S Christin, \u00c9 Hervet, N Lecomte\u00a0- Methods in Ecology and\u00a0\u2026, 2021 - Wiley Online Library", "snippet": "\u2026 Adding model verification to a deep learning model development \u2026 their deep learning model \ncan have and try to find, for each, a solution to help them navigate the steps of deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=670449110443086556&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:3NLv6-npTQkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=670449110443086556&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] VeeAlign: a supervised deep learning approach to ontology alignment.", "title_link": "https://moex.inria.fr/files/reports/ISWC2020-OM-ws.pdf#page=225", "publication_info": "V Iyer, A Agarwal, H Kumar\u00a0- OM@ ISWC, 2020 - moex.inria.fr", "snippet": "\u2026 Lastly and mostx importantly, we plan on targeting the biomedical tracks (such as Anatomy, \nLargeBio and Biodiversity) and adapting VeeAlign to use biomedical background knowledge\u2026", "cited_by": "https://scholar.google.com/scholar?cites=1152782954355679937&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:weJ-Qf2B_w8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1152782954355679937&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Gear-induced concept drift in marine images and its effect on deep learning classification", "title_link": "https://www.frontiersin.org/articles/10.3389/fmars.2020.00506/full", "publication_info": "D Langenk\u00e4mper, R Van Kevelaer, A Purser\u2026\u00a0- Frontiers in Marine\u00a0\u2026, 2020 - frontiersin.org", "snippet": "\u2026 them an appropriate choice for testing deep learning architectures in marine imaging. \u2026 \nThe results show limitations for the generalization power of a chosen up-to-date deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1671347387660451655&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Rz_HCZjRMRcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1671347387660451655&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automatic mapping of center pivot irrigation systems from satellite images using deep learning", "title_link": "https://www.mdpi.com/635878", "publication_info": "M Saraiva, \u00c9 Protas, M Salgado, C Souza Jr\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "\u2026 India, the increase of irrigated agriculture intensified the process of soil salinization and \nwaterlogging due to intensive seepage into the ground water, resulting in declining biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4762056778409870595&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:A4Vc1Wg5FkIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4762056778409870595&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "imageseg: an R package for deep learning-based image segmentation", "title_link": "https://www.biorxiv.org/content/10.1101/2021.12.16.469125.abstract", "publication_info": "J Niedballa, J Axtner, TF D\u00f6bert, A Tilker, A Nguyen\u2026\u00a0- bioRxiv, 2021 - biorxiv.org", "snippet": "\u2026 for a number of ecological applications from biodiversity surveys to forest monitoring and \nground-\u2026 Both measures are thus related to carbon sequestration and storage, biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:Mbh9KeIV0FgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=6399639131596372017&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6399639131596372017&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] On the impact of Citizen Science-derived data quality on deep learning based classification in marine images", "title_link": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0218086", "publication_info": "D Langenk\u00e4mper, E Simon-Lledo, B Hosking\u2026\u00a0- PloS One, 2019 - journals.plos.org", "snippet": "\u2026 It allowed us to analyze the relationship between the outcome of a citizen science study \nand the quality of the classifications of a deep learning megafauna classifier. The results show \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10306865227987298840&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:GCoCFlFXCY8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10306865227987298840&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "\u2026\u00a0image classification: The latest advances based on mathematical morphology, Markov random fields, segmentation, sparse representation, and deep learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/8474403/", "publication_info": "P Ghamisi, E Maggiori, S Li, R Souza\u2026\u00a0- \u2026\u00a0and remote sensing\u00a0\u2026, 2018 - ieeexplore.ieee.org", "snippet": "\u2026 (SR), and deep learning are addressed, with an emphasis on their methodological \nfoundations. We also present examples of experimental results using three benchmark hyperspectral \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17194708644092713760&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=G2V4oBIAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=17194708644092713760&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Challenges in the deep learning-based semantic segmentation of benthic communities from Ortho-images", "title_link": "https://link.springer.com/article/10.1007/s12518-020-00331-6", "publication_info": "G Pavoni, M Corsini, N Pedersen, V Petrovic\u2026\u00a0- Applied Geomatics, 2021 - Springer", "snippet": "\u2026 This paper focuses on the application of deep learning techniques to multi-view stereo \nreconstruction by-products (registered images, point clouds, ortho-projections), considering the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15177474073041212295&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:h5NSd0E4odIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15177474073041212295&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] A deep learning-based forecasting model for renewable energy scenarios to guide sustainable energy policy: A case study of Korea", "title_link": "https://www.sciencedirect.com/science/article/pii/S1364032120300228", "publication_info": "KJ Nam, S Hwangbo, CK Yoo\u00a0- Renewable and Sustainable Energy\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 and evaluates deep learning models and conventional statistical models. The deep learning \n\u2026 Comparison and evaluation of the forecasting models are significant since deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2255164184900752993&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:YVYxt-DzSx8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2255164184900752993&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[BOOK][B] Advances in Forest Management Under Global Change", "title_link": "https://books.google.com/books?hl=en&lr=&id=vLEtEAAAQBAJ&oi=fnd&pg=PP12&dq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&ots=AtKNRthaim&sig=Y6KPZIwtbM9j4tHOh0IyWlu5tWg", "publication_info": "L Zhang - 2020 - books.google.com", "snippet": "\u2026 One negative effect of global change could be loss of biodiversity, which could be \u2026 successful \nand advanced forest management, such as deep learning in plant disease prevention, and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5154088940469177609&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:CU1vdZUAh0cJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Active deep learning for hyperspectral image classification with uncertainty learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/9319397/", "publication_info": "Z Lei, Y Zeng, P Liu, X Su\u00a0- IEEE geoscience and remote\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 Moreover, with the rapid development of deep learning (DL), the accuracy of HSI classification \nhas been dramatically improved [2]. However, deep network training is quite expensive \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13015140555073451824&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:MPfurmARn7QJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13015140555073451824&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep-learning-based information mining from ocean remote-sensing imagery", "title_link": "https://academic.oup.com/nsr/article-abstract/7/10/1584/5809984", "publication_info": "X Li, B Liu, G Zheng, Y Ren, S Zhang\u2026\u00a0- National Science\u00a0\u2026, 2020 - academic.oup.com", "snippet": "\u2026 Deep learning\u2014a powerful technology recently emerging in \u2026 systematically reviewed two \ndeep-learning frameworks that \u2026 to show how effective these deep-learning frameworks are. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11722673334521794789&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:5ZAd0klNr6IJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11722673334521794789&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Identification of animal individuals using deep learning: A case study of giant panda", "title_link": "https://www.sciencedirect.com/science/article/pii/S000632071931609X", "publication_info": "J Hou, Y He, H Yang, T Connor, J Gao, Y Wang\u2026\u00a0- Biological\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 Here, we applied the deep learning technology and developed a novel face-identification \nmodel based on convolutional neural network to identify giant panda individuals. The model \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9878244398421899135&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:f_dtdPGSFokJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9878244398421899135&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Improving landslide detection on SAR data through deep learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/9610078/", "publication_info": "L Nava, O Monserrat, F Catani\u00a0- IEEE Geoscience and Remote\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 learning methods and deeplearning convolutional neural \u2026 Catani, \u201cLandslide detection by \ndeep learning of non-nadiral \u2026 and biodiversity distributions,\u201d PLOS Biol., vol. 14, no. 3, Mar. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=160195828852465492&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:VB9A8UEhOQIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=160195828852465492&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Urban tree species classification using a WorldView-2/3 and LiDAR data fusion approach and deep learning", "title_link": "https://www.mdpi.com/427516", "publication_info": "S Hartling, V Sagan, P Sidike, M Maimaitijiang\u2026\u00a0- Sensors, 2019 - mdpi.com", "snippet": "\u2026 the recent evolution of deep learning within remote sensing for \u2026 Additionally, contemporary \ndeep learning methods are \u2026 potential of a novel deep learning method, Dense Convolutional \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17670095034861385331&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:c3ZOZNDJOPUJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17670095034861385331&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep learning prediction of likelihood of ICU admission and mortality in COVID-19 patients using clinical variables", "title_link": "https://peerj.com/articles/10337/", "publication_info": "X Li, P Ge, J Zhu, H Li, J Graham, A Singer\u2026\u00a0- PeerJ, 2020 - peerj.com", "snippet": "\u2026 The goal of this study was to develop a deep-learning algorithm (in contrast to previous \nmethods) to identify the top, statistically significant predictors amongst the large array of clinical \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14626276491387589725&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:XdTNv_n4-soJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14626276491387589725&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Modeling Deep into Learning: A framework-based approach towards image detection", "title_link": "https://www.gjeis.com/index.php/GJEIS/article/view/447", "publication_info": "S Gupta, N Kashyap\u00a0- Global Journal of Enterprise Information System, 2020 - gjeis.com", "snippet": "\u2026 task performed in the field of biodiversity. With the innovation in technology, specie detection \ncan be done using deep learning. As we all know that Deep Learning is a field of machine \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:l-vQfSD8QZ8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=11475730541996731287&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11475730541996731287&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community", "title_link": "https://hess.copernicus.org/articles/22/5639/2018/", "publication_info": "C Shen, E Laloy, A Elshorbagy, A Albert\u2026\u00a0- Hydrology and Earth\u00a0\u2026, 2018 - hess.copernicus.org", "snippet": "\u2026 Deep learning (DL) is a suite of tools centered on artfully designed large-size artificial \u2026 \nReaders who are less familiar with machine learning or deep learning are referred to a companion \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11074478601954392589&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=flJP1GsAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=11074478601954392589&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Identifying of Quercus vulcanica and Q. frainetto growing in different environments through deep learning analysis", "title_link": "https://link.springer.com/article/10.1007/s10661-021-09565-2", "publication_info": "AH I\u015f\u0131k, C Y\u00fcceda\u011f, \u00d6C Eskicioglu\u2026\u00a0- Environmental Monitoring\u00a0\u2026, 2021 - Springer", "snippet": "\u2026 performance in the deep learning model. Accuracy rates of deep learning architectures varied \nfrom 79% (Xception) to 95% (VGG16). The VGG16 deep learning model provided superior \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:oG_7rvpQE_AJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=17299259631267966880&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17299259631267966880&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] DeepBindRG: a deep learning based method for estimating effective protein\u2013ligand affinity", "title_link": "https://peerj.com/articles/7362/", "publication_info": "H Zhang, L Liao, KM Saravanan, P Yin, Y Wei\u00a0- PeerJ, 2019 - peerj.com", "snippet": "\u2026 affinity indicates that deep learning approach can \u2026 deep learning method \u201cpafnucy\u201d, the \nadvantage and limitation of both methods have provided clues for improving the deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4055929002647357284&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ZAcATfCNSTgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4055929002647357284&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "DeepForest: A Python package for RGB deep learning tree crown delineation", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13472", "publication_info": "BG Weinstein, S Marconi\u2026\u00a0- Methods in Ecology\u00a0\u2026, 2020 - Wiley Online Library", "snippet": "\u2026 trees in high resolution RGB imagery using deep learning. \u2026 While deep learning has proven \nhighly effective in a range of \u2026 of using and retraining deep learning models for a range of \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4018186955550406830&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:rriwLr93wzcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4018186955550406830&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Monitoring early stage invasion of exotic Spartina alterniflora using deep-learning super-resolution techniques based on multisource high-resolution satellite\u00a0\u2026", "title_link": "https://www.sciencedirect.com/science/article/pii/S0303243419313649", "publication_info": "M Chen, Y Ke, J Bai, P Li, M Lyu, Z Gong\u2026\u00a0- International Journal of\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 The YRD has been one of the areas with the richest biodiversity in the world. In 1992, the \nYRD National Nature Reserve was founded to conserve the estuarine wetland ecosystem and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11671964505205781861&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ZTXCc-Al-6EJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11671964505205781861&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Analyzing the effects of Green View Index of neighborhood streets on walking time using Google Street View and deep learning", "title_link": "https://www.sciencedirect.com/science/article/pii/S0169204620301018", "publication_info": "D Ki, S Lee\u00a0- Landscape and Urban Planning, 2021 - Elsevier", "snippet": "\u2026 This study utilized Google Street View (GSV) and deep learning to calculate the GVI by \nsemantic segmentation, referring to greenness from the visual perspective of pedestrians. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2955940777176565174&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:toWzwHmcBSkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2955940777176565174&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn", "title_link": "https://www.sciencedirect.com/science/article/pii/S0924271619300115", "publication_info": "R Interdonato, D Ienco, R Gaetano, K Ose\u00a0- ISPRS journal of\u00a0\u2026, 2019 - Elsevier", "snippet": "\u2026 In this work, we propose the first deep learning architecture for the analysis of \u2026 a deep \nlearning architecture for the analysis of SITS data, namely DuPLO (DUal view Point deep Learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1700842213305290062&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Tg0NR_uamhcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1700842213305290062&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Flower mapping in grasslands with drones and deep learning", "title_link": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864122/", "publication_info": "J Gallmann, B Sch\u00fcpbach, K Jacot\u2026\u00a0- Frontiers in plant\u00a0\u2026, 2021 - ncbi.nlm.nih.gov", "snippet": "\u2026 images by using deep learning (Faster R-CNN) object detection approach, which was trained \nand evaluated on data from five flights at two sites. Our deep learning network was able to \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13724727143249702617&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:2W6PvJ4GeL4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13724727143249702617&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for prediction of the air quality response to emission changes", "title_link": "https://pubs.acs.org/doi/abs/10.1021/acs.est.0c02923", "publication_info": "J Xing, S Zheng, D Ding, JT Kelly, S Wang\u2026\u00a0- \u2026\u00a0science & technology, 2020 - ACS Publications", "snippet": "\u2026 Here, we demonstrate a novel method that combines deep learning approaches with \nchemical \u2026 Our results demonstrate the utility of deep learning approaches for capturing the \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11402756802303017744&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=3ViF3lIAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=11402756802303017744&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Using Artificial Intelligence to Downscale Ecosystem-Related Essential Biodiversity Variables in Mountain Environments", "title_link": "https://bia.unibz.it/esploro/outputs/conferencePresentation/Using-Artificial-Intelligence-to-Downscale-Ecosystem-Related/991006133719101241", "publication_info": "D Frisinghelli, M Claus, A Jacob, R Sayre, C Adler\u2026\u00a0- ESA Phi-week\u00a0\u2026, 2021 - bia.unibz.it", "snippet": "\u2026 The algorithms are implemented in the Microsoft Azure High Performance Computing (HPC) \ncloud platform, where the computationally expensive deep learning algorithms can make \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comhttps://scholar.googleusercontent.com/scholar?q=cache:KXrGk_XOlZsJ:scholar.google.com/+biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[HTML][HTML] Integrating drone-borne thermal imaging with artificial intelligence to locate bird nests on agricultural land", "title_link": "https://www.nature.com/articles/s41598-020-67898-3", "publication_info": "A Santangeli, Y Chen, E Kluen, R Chirumamilla\u2026\u00a0- Scientific reports, 2020 - nature.com", "snippet": "\u2026 allow very limited monitoring of biodiversity. This is partly due \u2026 Therefore, there is an urgent \nneed for efficient biodiversity \u2026 a nest, we trained a deep learning model (more details in \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10874628720009618573&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:jSRvYDRx6pYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10874628720009618573&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[CITATION][C] Using deep learning to identify animals in camera-trap images for bio-diversity monitoring", "title_link": "http://oro.open.ac.uk/71362/", "publication_info": "K Waddington - 2020 - oro.open.ac.uk", "snippet": "Using deep learning to identify animals in camera-trap images for bio-diversity monitoring - \u2026 \ndeep learning; machine learning; biodiversity monitoring;image recognition architectures;\u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comhttp://scholar.googleusercontent.com/scholar?q=cache:WJl-bVMVbCsJ:scholar.google.com/+biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Fast, scalable, and automated identification of articles for biodiversity and macroecological datasets", "title_link": "https://onlinelibrary.wiley.com/doi/abs/10.1111/geb.13219", "publication_info": "R Cornford, S Deinet, A De Palma\u2026\u00a0- Global Ecology and\u00a0\u2026, 2021 - Wiley Online Library", "snippet": "\u2026 We have also not addressed how the architecture of deep-learning networks could influence \nmodel performance. While a thorough exploration of CNN hyperparameters would be \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5797089279504623697&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:USgZRPxlc1AJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5797089279504623697&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep learning for a sustainability mindset", "title_link": "https://www.sciencedirect.com/science/article/pii/S147281171730304X", "publication_info": "J Hermes, I Rimanoczy\u00a0- The International Journal of Management\u00a0\u2026, 2018 - Elsevier", "snippet": "\u2026 Addressing the knowledge, systems thinking, emotional aspects, the tacit paradigms and the \nvalues we adhere to, students were led on a journey of discovery that created deep learning\u2026", "cited_by": "https://scholar.google.com/scholar?cites=14835027650431362782&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:3iYPeQyb4M0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14835027650431362782&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for microalgae classification", "title_link": "https://ieeexplore.ieee.org/abstract/document/8260609/", "publication_info": "I Correa, P Drews, S Botelho\u2026\u00a0- 2017 16th IEEE\u00a0\u2026, 2017 - ieeexplore.ieee.org", "snippet": "\u2026 We proposed a deep learning technique to solve the problem. We also created a classified \ndataset that allow us to adopt this technique. To the best of our knowledge, the present work \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10838316584619610831&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:zxJ6hYJvaZYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10838316584619610831&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Leaf segmentation and classification with a complicated background using deep learning", "title_link": "https://www.mdpi.com/881490", "publication_info": "K Yang, W Zhong, F Li\u00a0- Agronomy, 2020 - mdpi.com", "snippet": "\u2026 Recently, urbanization and biodiversity loss have made plant classification a significant \nproblem for many professionals such as agronomists, gardeners, and foresters. Classification of \u2026", "cited_by": "https://scholar.google.com/scholar?cites=12664754937120209245&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:XblsuoM_wq8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12664754937120209245&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "AyurLeaf: a deep learning approach for classification of medicinal plants", "title_link": "https://ieeexplore.ieee.org/abstract/document/8929394/", "publication_info": "MR Dileep, PN Pournami\u00a0- TENCON 2019-2019 IEEE Region\u00a0\u2026, 2019 - ieeexplore.ieee.org", "snippet": "\u2026 Plants play a crucial role in preserving life and maintaining biodiversity on earth by facilitating \nair and water for living beings. Medicinal plants, one of the important class of plants, serve \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8567471698649405241&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Odc1FR7G5XYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Monitoring and mapping the critically endangered Clanwilliam cedar using aerial imagery and deep learning", "title_link": "https://open.uct.ac.za/handle/11427/35622", "publication_info": "B Hadebe - 2021 - open.uct.ac.za", "snippet": "\u2026 to assess whether deep learning can \u2026 deep learning has previously been applied to remote \nsensing problems, with a particular focus on problems involving conservation and biodiversity\u2026", "cited_by": "https://scholar.google.com/scholar?q=related:9aXi6ZckDPMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=17513413285819622901&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17513413285819622901&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Smart farming becomes even smarter with deep learning\u2014a bibliographical analysis", "title_link": "https://ieeexplore.ieee.org/abstract/document/9108212/", "publication_info": "Z \u00dcnal\u00a0- IEEE Access, 2020 - ieeexplore.ieee.org", "snippet": "\u2026 Deep learning networks that do not need human intervention while performing \u2026 deep \nlearning in agricultural applications. This bibliography reviews the potential of using deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3583990639178208084&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:VNOKXn_kvDEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=3583990639178208084&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Learning niche features to improve image-based species identification", "title_link": "https://www.sciencedirect.com/science/article/pii/S157495412100008X", "publication_info": "C Lin, X Huang, J Wang, T Xi, L Ji\u00a0- Ecological Informatics, 2021 - Elsevier", "snippet": "\u2026 conserve biodiversity with saving much time and effort. But image-based deep learning \nmethods \u2026 niche model and image-based deep learning model together expanding from the joint \u2026", "cited_by": "https://scholar.google.com/scholar?cites=920535473752344371&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:M4cn3CJmxgwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=920535473752344371&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] \u2026\u00a0of AOP relevant to microplastics based on toxicity mechanisms of chemical additives using ToxCast\u2122 and deep learning models combined approach", "title_link": "https://www.sciencedirect.com/science/article/pii/S0160412019344630", "publication_info": "J Jeong, J Choi\u00a0- Environment international, 2020 - Elsevier", "snippet": "\u2026 Deep learning artificial neural network models were further \u2026 Using both the ToxCast database \nand deep learning models, \u2026 in vitro toxicity database and deep learning model combined \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17911978845724980179&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:07O_w9shlPgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17911978845724980179&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A novel approach for scene classification from remote sensing images using deep learning methods", "title_link": "https://www.tandfonline.com/doi/abs/10.1080/22797254.2020.1790995", "publication_info": "X Xu, Y Chen, J Zhang, Y Chen\u2026\u00a0- European Journal of\u00a0\u2026, 2021 - Taylor & Francis", "snippet": "\u2026 From the above studies, it is evident that deep learning could be the most effective tool \nfor analyzing the remote sensed images, So in this study, a deep learning-based image \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15214554850720604173&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:DeDlzAb1JNMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15214554850720604173&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep-learning-based burned area mapping using the synergy of Sentinel-1&2 data", "title_link": "https://www.sciencedirect.com/science/article/pii/S0034425721002959", "publication_info": "Q Zhang, L Ge, R Zhang, GI Metternicht, Z Du\u2026\u00a0- Remote Sensing of\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 This paper presents a deep-learning-based BA mapping strategy applied to a synergistic \ndataset provided by Sentinel-1 and Sentinel-2 satellites. This process relies on the construction \u2026", "cited_by": "https://scholar.google.com/scholar?cites=999044096039767786&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=xLdoc44AAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=999044096039767786&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Phenotypic analysis of microalgae populations using label-free imaging flow cytometry and deep learning", "title_link": "https://pubs.acs.org/doi/abs/10.1021/acsphotonics.1c00220", "publication_info": "C Is\u0327\u0131l, K de Haan, Z Gorocs, HC Koydemir\u2026\u00a0- ACS\u00a0\u2026, 2021 - ACS Publications", "snippet": "\u2026 Microalgae form a particularly rich source of information about the long-term effects of \npollution on biodiversity in the marine environment due to their short generation times and high \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14391539660784797695&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=TK6ctt4AAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=14391539660784797695&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Evaluation of riparian tree cover and shading in the Chauga river watershed using LiDAR and deep learning land cover classification", "title_link": "https://www.mdpi.com/2072-4292/13/20/4172", "publication_info": "MM Bolick, CJ Post, EA Mikhailova, HA Zurqani\u2026\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 This study used supervised deep learning to accurately \u2026 The deep learning classifications \nproduced land cover maps \u2026 This study demonstrates the accurate application of deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5176957491598856538&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:WhEM8Gg_2EcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5176957491598856538&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Green digitization: Online botanical collections data answering real\u2010world questions", "title_link": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5851568/", "publication_info": "PS Soltis, G Nelson, SA James\u00a0- Applications in Plant Sciences, 2018 - ncbi.nlm.nih.gov", "snippet": "\u2026 components; the use of deep learning in specimen identification from \u2026 biodiversity specimens \nacross the internet has been a hotly debated subject. Although the majority of biodiversity \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2200329847458055503&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:T0VtolYkiR4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2200329847458055503&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Parsing Birdsong with Deep Audio Embeddings", "title_link": "https://arxiv.org/abs/2108.09203", "publication_info": "I Tolkova, B Chu, M Hedman, S Kahl\u2026\u00a0- arXiv preprint arXiv\u00a0\u2026, 2021 - arxiv.org", "snippet": "\u2026 efforts and in understanding biodiversity loss. The automation \u2026 analytical tools, such as \ndeep learning. However, machine \u2026 Most deep learning approaches for audio analysis will first \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1862584868706411200&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:wGJD1xE72RkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1862584868706411200&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "3D fine-scale terrain variables from underwater photogrammetry: A new approach to benthic microhabitat modeling in a circalittoral Rocky shelf", "title_link": "https://www.mdpi.com/785934", "publication_info": "E Prado, A Rodr\u00edguez-Basalo, A Cobo, P R\u00edos\u2026\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "\u2026 To perform this work automatically and unsupervised, recent deep-learning algorithms for \u2026 \ninfluences key ecological processes, ecosystem biodiversity and resilience. In this environment\u2026", "cited_by": "https://scholar.google.com/scholar?cites=165696123187295985&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:8fY8A7-rTAIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=165696123187295985&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Using deep learning to quantify the beauty of outdoor places", "title_link": "https://royalsocietypublishing.org/doi/abs/10.1098/rsos.170170", "publication_info": "CI Seresinhe, T Preis, HS Moat\u00a0- Royal Society open\u00a0\u2026, 2017 - royalsocietypublishing.org", "snippet": "\u2026 For all our experiments, we use the deep learning framework Caffe [46]. For AlexNet, \nVGG16 and GoogleNet, training is performed by stochastic gradient descent (SGD) with mini-batch \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11178320796367208324&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:hD_U_IlfIZsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11178320796367208324&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Social media and deep learning capture the aesthetic quality of the landscape", "title_link": "https://www.nature.com/articles/s41598-021-99282-0", "publication_info": "I Havinga, D Marcos, PW Bogaart, L Hein, D Tuia\u00a0- Scientific reports, 2021 - nature.com", "snippet": "\u2026 deep learning have enabled large-scale analysis of the imagery uploaded to these platforms. \nIn this study, we test the accuracy of Flickr and deep learning\u2026 media and deep learning can \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2650130501346507724&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=2wj1RaIAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=2650130501346507724&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Semantic boosting: Enhancing deep learning based LULC classification", "title_link": "https://www.mdpi.com/2072-4292/13/16/3197", "publication_info": "M Mc Cutchan, AJ Comber, I Giannopoulos\u2026\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 In contrast, we employ deep learning to determine the relationship between LULC classes \n\u2026 Finally, they use the GSCM to predict urban growth for Europe, by means of deep learning. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1478027560392649652&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:tOtwOTwCgxQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1478027560392649652&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Long-term Burned Area Reconstruction through Deep Learning", "title_link": "https://s3.us-east-1.amazonaws.com/climate-change-ai/papers/icml2021/72/paper.pdf", "publication_info": "S Lampe, B Le Saux, I Vanderkelen, W Thiery - s3.us-east-1.amazonaws.com", "snippet": "\u2026 While regular-sized wildfires sustain biodiversity and ecosystem health, megafires have \u2026 \nFire management for biodiversity conservation: Key research questions and our capacity to \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:oPK_6bo7Fj0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/citations?user=dWsYitYAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=4401771359772865184&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Bird sound detection based on binarized convolutional neural networks", "title_link": "https://link.springer.com/chapter/10.1007/978-981-13-8707-4_6", "publication_info": "J Song, S Li\u00a0- Proceedings of the 6th conference on sound and music\u00a0\u2026, 2019 - Springer", "snippet": "\u2026 is helpful for monitoring biodiversity and in this regard, deep learning networks have shown \n\u2026 In order to solve the challenge of implementing bird sound detection based on deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16901156046596544516&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:BBjV0uD3jOoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16901156046596544516&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Species Detection and Segmentation of Multi-specimen Historical Herbaria", "title_link": "https://biss.pensoft.net/article/74060/download/pdf/", "publication_info": "KKT Chandrasekar, K Milleville\u2026\u00a0- Biodiversity Information\u00a0\u2026, 2021 - biss.pensoft.net", "snippet": "\u2026 Younis S, Schmidt M, Weiland C, Dressler S, Seeger B, Hickler T (2020) Detection and \nannotation of plant organs from digitised herbarium scans using deep learning. Biodiversity Data \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:Fms4vZVdB-IJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=16287089475114789654&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16287089475114789654&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] DeepCropMapping: A multi-temporal deep learning approach with improved spatial generalizability for dynamic corn and soybean mapping", "title_link": "https://www.sciencedirect.com/science/article/pii/S0034425720303163", "publication_info": "J Xu, Y Zhu, R Zhong, Z Lin, J Xu, H Jiang\u2026\u00a0- Remote Sensing of\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 A deep learning approach, named DeepCropMapping (DCM)\u2026 integration of deep learning \nand remote sensing time series. \u2026 are three prominent deep learning architectures that can \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8167539117762108686&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Dl1R243tWHEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8167539117762108686&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "An overview on deep learning-based approximation methods for partial differential equations", "title_link": "https://arxiv.org/abs/2012.12348", "publication_info": "C Beck, M Hutzenthaler, A Jentzen\u2026\u00a0- arXiv preprint arXiv\u00a0\u2026, 2020 - arxiv.org", "snippet": "\u2026 evaluation of financial products such as financial derivative contracts, and in the \napproximative description of the distribution of species in ecosystems to model biodiversity under \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4321202990337827247&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ryFxmTn_9zsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4321202990337827247&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Fast enhanced CT metal artifact reduction using data domain deep learning", "title_link": "https://ieeexplore.ieee.org/abstract/document/8815915/", "publication_info": "MU Ghani, WC Karl\u00a0- IEEE Transactions on Computational\u00a0\u2026, 2019 - ieeexplore.ieee.org", "snippet": "\u2026 Motivated primarily by security applications, we present a new deep-learning-based metal \nartifact reduction approach that tackles the problem in the projection data domain. We treat \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17179367683264896319&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:P13UQuNfae4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17179367683264896319&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Accuracy of deep learning, a machine learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting idiopathic macular holes", "title_link": "https://peerj.com/articles/5696/", "publication_info": "T Nagasawa, H Tabuchi, H Masumoto, H Enno, M Niki\u2026\u00a0- PeerJ, 2018 - peerj.com", "snippet": "\u2026 With the deep learning model, the approach is different from the approach \u2026 deep learning. \nAlthough the diagnostic ability of using a wide angle ocular fundus camera and deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=12624064986762122034&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:MhNnZTiwMa8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12624064986762122034&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Trees outside of forests as natural climate solutions", "title_link": "https://www.nature.com/articles/s41558-021-01230-3", "publication_info": "DL Skole, C Mbow, M Mugabowindekwe\u2026\u00a0- Nature Climate\u00a0\u2026, 2021 - nature.com", "snippet": "\u2026 of biodiversity and \u2026 , deep learning, which has emerged as a disruptive technology in \ndifferent fields of object detection, is increasingly used with satellite imagery. Deep learning uses \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10214904370377830570&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:qrD0amehwo0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10214904370377830570&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "\u2026\u00a0Analysis of the Ecosystem Services in the Guangdong-Hong Kong-Macao Greater Bay Area Using Sentinel-1 and Sentinel-2 Imagery Based on Deep Learning\u00a0\u2026", "title_link": "https://www.mdpi.com/1160830", "publication_info": "D Wen, S Ma, A Zhang, X Ke\u00a0- Sustainability, 2021 - mdpi.com", "snippet": "\u2026 With the support of Sentinel-1 SAR and Sentinel-2 optical remote sensing data, we \nproposed a deep learning-based land cover mapping framework to generate a 10 m spatial \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9981099028853095608&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:uPzIQq_8g4oJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9981099028853095608&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Climate-based regionalization and inclusion of spectral indices for enhancing transboundary land-use/cover classification using deep learning and machine learning", "title_link": "https://www.mdpi.com/2072-4292/13/24/5054", "publication_info": "B Kavhu, ZE Mashimbye, L Luvuno\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 Unsustainable utilization of natural resources across drainage basins globally threatens \nlivelihoods and biodiversity. Changes in land use (defined as the function of surface cover) and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=12917852771792616061&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:fXp-e6duRbMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12917852771792616061&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Jellytoring: Real-time jellyfish monitoring based on deep learning object detection", "title_link": "https://www.mdpi.com/668384", "publication_info": "M Martin-Abadal, A Ruiz-Frau, H Hinz, Y Gonzalez-Cid\u00a0- Sensors, 2020 - mdpi.com", "snippet": "\u2026 Deep learning based frameworks for image processing and object detection specifically, \nmostly rely on region-based Convolutional Neural Networks (CNN) like R-CNN [29] or its \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7277577304632414260&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:NFAPFAAm_2QJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7277577304632414260&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Using Computer Vision to Quantify Coral Reef Biodiversity", "title_link": "https://scholarworks.sjsu.edu/etd_projects/711/", "publication_info": "N Bhodia - 2019 - scholarworks.sjsu.edu", "snippet": "\u2026 be to first go for the best technique available in CV-deep learning (DL)-and that is what Dr. \u2026 \nThe \u201cdeep\u201d in \u201cdeep learning\u201d comes from the fact that the ANNs trained with DL algorithms \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11886462168553579901&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:fWXBeF0y9aQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11886462168553579901&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "The Premium of Public Perceived Greenery: A Framework Using Multiscale GWR and Deep Learning", "title_link": "https://www.mdpi.com/1163616", "publication_info": "Y Zhang, X Fu, C Lv, S Li\u00a0- \u2026\u00a0Journal of Environmental Research and Public\u00a0\u2026, 2021 - mdpi.com", "snippet": "\u2026 Urban parks and forests provide essential ecological benefits in maintaining biodiversity \nand performing carbon fixation [2,3]. Some scattered green spaces, such as road greenery [4] \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5181378214859098622&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:_smfxwj050cJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5181378214859098622&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Repurposing a deep learning network to filter and classify volunteered photographs for land cover and land use characterization", "title_link": "https://www.tandfonline.com/doi/abs/10.1080/10095020.2017.1373955", "publication_info": "L Tracewski, L Bastin, CC Fonte\u00a0- Geo-spatial information science, 2017 - Taylor & Francis", "snippet": "This paper extends recent research into the usefulness of volunteered photos for land cover \nextraction, and investigates whether this usefulness can be automatically assessed by an \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1908856020120585908&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:tEanzm-efRoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=1908856020120585908&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning based 3D point cloud regression for estimating forest biomass", "title_link": "https://arxiv.org/abs/2112.11335", "publication_info": "S Oehmcke, L Li, J Revenga, T Nord-Larsen\u2026\u00a0- arXiv preprint arXiv\u00a0\u2026, 2021 - arxiv.org", "snippet": "\u2026 We present deep learning systems for predicting wood volume, above-ground biomass (AGB\u2026 \nThey host about 80% of the terrestrial biodiversity and are major pillars of water and carbon \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9339372978537236201&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:6QaY6j0enIEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9339372978537236201&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Individual Sick Fir Tree (Abies mariesii) Identification in Insect Infested Forests by Means of UAV Images and Deep Learning", "title_link": "https://www.mdpi.com/959834", "publication_info": "HT Nguyen, ML Lopez Caceres, K Moritake, S Kentsch\u2026\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 While the tree species and the tree health problems studied are the same, the boreal conditions \nin Siberia decreased the biodiversity (where the forest studied in [9] is located) so only fir \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16777349177242536268&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:TMk7vi8e1egJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=16777349177242536268&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Sensor-based risk perception ability network design for drivers in snow and ice environmental freeway: a deep learning and rough sets approach", "title_link": "https://link.springer.com/article/10.1007/s00500-017-2850-x", "publication_info": "W Zhao, L Xu, J Bai, M Ji, T Runge\u00a0- Soft computing, 2018 - Springer", "snippet": "\u2026 This study sets forth an automatic evaluation network of the risk perceived ability for motorists \ndriving on the freeway in snow and ice environments, using a deep learning approach and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15182466536575257989&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:hc3S9t_0stIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15182466536575257989&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] piRNN: deep learning algorithm for piRNA prediction", "title_link": "https://peerj.com/articles/5429/", "publication_info": "K Wang, J Hoeksema, C Liang\u00a0- PeerJ, 2018 - peerj.com", "snippet": "\u2026 In summary, we developed a deep learning program for identifying piRNAs based on CNN. \nThe major advantages of this program can be concluded as: (1) this is the first deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=12446773357094720558&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:LlRtJWzSu6wJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=12446773357094720558&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep learning based Sequential model for malware analysis using Windows exe API Calls", "title_link": "https://peerj.com/articles/cs-285/", "publication_info": "FO Catak, AF Yaz\u0131, O Elezaj, J Ahmed\u00a0- PeerJ Computer Science, 2020 - peerj.com", "snippet": "\u2026 by the deep learning method better than the F1 values obtained by the traditional methods. \nThis suggests that deep learning is \u2026 data classification algorithms used before deep learning. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=368470494918567917&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:7WfVf_YRHQUJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=368470494918567917&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Prediction of Genetic Groups within Brettanomyces bruxellensis through Cell Morphology Using a Deep Learning Tool", "title_link": "https://www.mdpi.com/2309-608X/7/8/581", "publication_info": "M Lebleux, E Denimal, D De Oliveira, A Marin\u2026\u00a0- Journal of Fungi, 2021 - mdpi.com", "snippet": "\u2026 The present study opens new perspectives for the use of deep-learning methods in \noenology to provide powerful, robust and timesaving analyses. The polymorphism of yeast cells \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9395794153317703173&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:BZ4xWwCRZIIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9395794153317703173&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning monitoring of woody vegetation density in a South African Savannah region", "title_link": "https://e-space.mmu.ac.uk/id/eprint/625304", "publication_info": "E Symeonakis, A Korkofigkas\u2026\u00a0- \u2026\u00a0Archives of the\u00a0\u2026, 2020 - e-space.mmu.ac.uk", "snippet": "\u2026 Savannah ecoregions are important ecosystems with high biodiversity. They provide a \nnumber of ecosystem services, eg grazing for pastoralist communities, or the supply of fuelwood, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=440893006394751803&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:O_scdtpdHgYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=440893006394751803&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Combining high-throughput imaging flow cytometry and deep learning for efficient species and life-cycle stage identification of phytoplankton", "title_link": "https://link.springer.com/article/10.1186/s12898-018-0209-5", "publication_info": "S Dunker, D Boho, J W\u00e4ldchen, P M\u00e4der\u00a0- BMC ecology, 2018 - Springer", "snippet": "\u2026 images (two or four images per case) taken with the ImageStream \u00aeX MK II (\u00d760 magnification) \nof each phytoplankton species used in this study for training of the deep learning network \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3322050235111502756&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=LPzoSrsAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=3322050235111502756&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level\u00a0\u2026", "title_link": "https://www.sciencedirect.com/science/article/pii/S0022169421002432", "publication_info": "R Barzegar, MT Aalami, J Adamowski\u00a0- Journal of Hydrology, 2021 - Elsevier", "snippet": "\u2026 Providing strong support for global biodiversity, lakes harbor important ecosystems. Amongst \nthe most important lacustrine physical parameters, water level (WL) has significant socio-\u2026", "cited_by": "https://scholar.google.com/scholar?cites=2942342795281743595&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:674y4C5N1SgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2942342795281743595&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Identifying and mapping individual plants in a highly diverse high-elevation ecosystem using UAV imagery and deep learning", "title_link": "https://www.sciencedirect.com/science/article/pii/S0924271620302720", "publication_info": "C Zhang, PM Atkinson, C George, Z Wen\u2026\u00a0- ISPRS Journal of\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 This is true even for deep learning based semantic segmentation and classification methods. \nIn this research, a novel Scale Sequence Residual U-Net (SS Res U-Net) deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14437855640868094031&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:TwBQ2DWRXcgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14437855640868094031&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Mapping large-scale mangroves along the maritime silk road from 1990 to 2015 using a novel deep learning model and landsat data", "title_link": "https://www.mdpi.com/958760", "publication_info": "Y Guo, J Liao, G Shen\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 In view of the capability of deep learning in processing massive data in recent years, we \ndeveloped a new deep learning model\u2014Capsules-Unet, which introduces the capsule concept \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5602052089517090736&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:sKfmyLF8vk0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5602052089517090736&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for natural sound classification", "title_link": "https://www.ingentaconnect.com/content/ince/incecp/2019/00000259/00000004/art00073", "publication_info": "I Diez Gaspon, I Saratxaga\u2026\u00a0- INTER-NOISE and\u00a0\u2026, 2019 - ingentaconnect.com", "snippet": "\u2026 Traditionally, classification of environmental sounds has been mainly based on statistical \nclassifiers but in the last years deep learning techniques have been introduced in this context \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5521807382295392045&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:La_Y845moUwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5521807382295392045&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Human microbiome aging clocks based on deep learning and tandem of permutation feature importance and accumulated local effects", "title_link": "https://www.biorxiv.org/content/10.1101/507780.abstract", "publication_info": "F Galkin, A Aliper, E Putin, I Kuznetsov, VN Gladyshev\u2026\u00a0- BioRxiv, 2018 - biorxiv.org", "snippet": "\u2026 Some studies indicate decreasing biodiversity in the elderly gut 11,12 . However, that is \nnot the case for all data sets, and elderly healthy people may have microbiomes as diverse as \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11090909261316684509&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=CosBFrUAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=11090909261316684509&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Review and evaluation of deep learning architectures for efficient land cover mapping with UAS hyper-spatial imagery: A case study over a wetland", "title_link": "https://www.mdpi.com/666276", "publication_info": "M Pashaei, H Kamangir, MJ Starek, P Tissot\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "Deep learning has already been proved as a powerful state-of-the-art technique for many \u2026 \nSome simple deep learning architectures perform comparable or even better than complex \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13646953902588560959&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=Itf5RrIAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=13646953902588560959&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Eelgrass Beds and Oyster Farming in a Lagoon Before and After The Great East Japan Earthquake of 2011: Potential for Applying Deep Learning at a Coastal Area", "title_link": "https://ieeexplore.ieee.org/abstract/document/8900354/", "publication_info": "T Yamakita\u00a0- \u2026\u00a02019-2019 IEEE International Geoscience and\u00a0\u2026, 2019 - ieeexplore.ieee.org", "snippet": "\u2026 This model, which uses deep learning, can detect the texture, shapes, and contrast of \u2026 \nthe different models of deep learning. As representative deep learning models for an image, a \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9904103079339505880&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:2DjixkZxcokJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[HTML][HTML] A practical method superior to traditional spectral identification: Two-dimensional correlation spectroscopy combined with deep learning to identify Paris\u00a0\u2026", "title_link": "https://www.sciencedirect.com/science/article/pii/S0026265X20332227", "publication_info": "JQ Yue, HY Huang, YZ Wang\u00a0- Microchemical Journal, 2021 - Elsevier", "snippet": "\u2026 In this study, a detailed study of FT-MIR 2DCOS combined with deep learning to identify \n12 Paris species has been first carried out. That is, synchronous and asynchronous 2DCOS \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7423146418387939547&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:2_C5h1ZQBGcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7423146418387939547&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Biodiversity image quality metadata augments Convolutional neural network classification of fish species", "title_link": "https://link.springer.com/chapter/10.1007/978-3-030-71903-6_1", "publication_info": "J Leipzig, Y Bakis, X Wang, M Elhamod\u2026\u00a0- \u2026\u00a0Conference on Metadata\u00a0\u2026, 2020 - Springer", "snippet": "\u2026 extensive growth in open science repositories, and, in particular, the underlying application \nof rich metadata has potential value for data mining, machine learning and deep learning (ML\u2026", "cited_by": "https://scholar.google.com/scholar?cites=227122053397205748&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:9NJl4U3mJgMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=227122053397205748&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Automatic detection and quantification of floating marine macro-litter in aerial images: Introducing a novel deep learning approach connected to a web\u00a0\u2026", "title_link": "https://www.sciencedirect.com/science/article/pii/S0269749121000683", "publication_info": "O Garcia-Garin, T Monle\u00f3n-Getino, P L\u00f3pez-Brosa\u2026\u00a0- Environmental\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 In this study, we applied CNN-based deep learning models to detect and quantify FMML \nin aerial images, we proposed their coupling to the AIImagePred library in R and their \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15846487422819461232&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:cGjZTloI6tsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15846487422819461232&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] A computer vision approach based on deep learning for the detection of dairy cows in free stall barn", "title_link": "https://www.sciencedirect.com/science/article/pii/S016816992100048X", "publication_info": "P Tassinari, M Bovo, S Benni, S Franzoni\u2026\u00a0- \u2026\u00a0and Electronics in\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 A computer vision system implemented through deep learning constitutes a suitable \u2026 of a \ncomputer vision system, based on deep learning techniques, for the automatic recognition of \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14748032601760294648&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:-GbNS4OJq8wJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14748032601760294648&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Exploitation of time series sentinel-2 data and different machine learning algorithms for detailed tree species classification", "title_link": "https://ieeexplore.ieee.org/abstract/document/9495140/", "publication_info": "Y Xi, C Ren, Q Tian, Y Ren, X Dong\u2026\u00a0- IEEE Journal of\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 ing data is of great significance to monitoring forest disturbances, biodiversity assessment, \u2026 \nthe application of deep learning. Our results show that the deep learning algorithm has higher \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17913532176627110112&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:4JBjzJqmmfgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17913532176627110112&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Automating the analysis of fish abundance using object detection: optimizing animal ecology with deep learning", "title_link": "https://www.frontiersin.org/articles/10.3389/fmars.2020.00429/full?utm_campaign=later-linkinbio-totally.unsupervised&utm_content=later-9494265&utm_medium=social&utm_source=instagram", "publication_info": "EM Ditria, S Lopez-Marcano, M Sievers\u2026\u00a0- Frontiers in Marine\u00a0\u2026, 2020 - frontiersin.org", "snippet": "\u2026 The use of deep learning to automate image processing has \u2026 accuracy and speed of deep \nlearning techniques against human \u2026 We show that deep learning can be a more accurate tool \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11739444018269942098&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:UnGQ6SLi6qIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11739444018269942098&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Mechanical control with a deep learning method for precise weeding on a farm", "title_link": "https://www.mdpi.com/2077-0472/11/11/1049", "publication_info": "CL Chang, BX Xie, SC Chung\u00a0- Agriculture, 2021 - mdpi.com", "snippet": "\u2026 The F1-score of the deep learning model designed in this research \u2026 , and the biodiversity of \nfarmland will be improved [64]. \u2026 ecosystem and increase the biodiversity of the farmland [64]. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7420418499276836826&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:2g8iXk-f-mYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7420418499276836826&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning approaches for improving prediction of daily stream temperature in data\u2010scarce, unmonitored, and dammed basins", "title_link": "https://onlinelibrary.wiley.com/doi/abs/10.1002/hyp.14400", "publication_info": "F Rahmani, C Shen, S Oliver, K Lawson\u2026\u00a0- Hydrological\u00a0\u2026, 2021 - Wiley Online Library", "snippet": "\u2026 Using modelled stream temperatures to predict macrospatial patterns of stream \ninvertebrate biodiversity. Freshwater Biology, 59(12), 2632\u2013 2644. https://doi.org/10.1111/fwb.12459 \u2026", "cited_by": "https://scholar.google.com/scholar?cites=1741778824040133881&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=-fjUvaoAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=1741778824040133881&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Pose estimation-dependent identification method for field moth images using deep learning architecture", "title_link": "https://www.sciencedirect.com/science/article/pii/S1537511015001026", "publication_info": "C Wen, D Wu, H Hu, W Pan\u00a0- biosystems engineering, 2015 - Elsevier", "snippet": "\u2026 A novel pose estimation-dependent automated identification method using deep learning \narchitecture is proposed in this paper for on-trap field moth sample images. To deal with \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17032893567021382910&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:_nxYf3T-YOwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17032893567021382910&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Monitoring agriculture areas with satellite images and deep learning", "title_link": "https://www.sciencedirect.com/science/article/pii/S1568494620305032", "publication_info": "TT Nguyen, TD Hoang, MT Pham, TT Vu\u2026\u00a0- Applied Soft\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 Then, we discuss the topic of deep learning methods for remote mapping. Finally, we \ncompare the functionality of our approach against existing solutions and classifiers. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4854782325887225737&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:iU9avM2mX0MJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4854782325887225737&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep learning techniques for automatic butterfly segmentation in ecological images", "title_link": "https://www.sciencedirect.com/science/article/pii/S0168169920313491", "publication_info": "H Tang, B Wang, X Chen\u00a0- Computers and Electronics in Agriculture, 2020 - Elsevier", "snippet": "\u2026 Deep learning based methods have achieved very inspiring segmentation results for \u2026 image \nusing deep learning. In our experiments, five state-of-the-art deep learning methods that are \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13644396966560706245&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:xa5E_r-iWr0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13644396966560706245&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Societal, economic, ethical and legal challenges of the digital revolution: from big data to deep learning, artificial intelligence, and manipulative technologies", "title_link": "https://link.springer.com/chapter/10.1007/978-3-319-90869-4_6", "publication_info": "D Helbing\u00a0- Towards digital enlightenment, 2019 - Springer", "snippet": "\u2026 Therefore, like our own brain, an artificial intelligence based on deep learning will sometimes \nsee \u2026 diversity must be protected in a similar way as we have learned to protect biodiversity. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8101176785690249430&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:1ki1XV0pbXAJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8101176785690249430&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Cyanobacteria cell prediction using interpretable deep learning model with observed, numerical, and sensing data assemblage", "title_link": "https://www.sciencedirect.com/science/article/pii/S0043135421006813", "publication_info": "JC Pyo, KH Cho, K Kim, SS Baek, G Nam, S Park\u00a0- Water Research, 2021 - Elsevier", "snippet": "\u2026 Deep learning attention models can process these intricate \u2026 However, deep learning \nattention models for predicting \u2026 Therefore, this study demonstrated that a deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=16667122633890084460&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=JarDiqkAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=16667122633890084460&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] A deep learning approach for mapping and dating burned areas using temporal sequences of satellite images", "title_link": "https://www.sciencedirect.com/science/article/pii/S0924271619303089", "publication_info": "MM Pinto, R Libonati, RM Trigo, IF Trigo\u2026\u00a0- ISPRS Journal of\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 Here, we explore a deep learning approach based on daily sequences of multi-spectral \u2026 \nThe obtained results are a strong indication of the advantage of deep learning approaches \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11579822373924465153&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=6dEC_LQAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=11579822373924465153&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Underwater live fish recognition by deep learning", "title_link": "https://link.springer.com/chapter/10.1007/978-3-319-94211-7_30", "publication_info": "AB Tamou, A Benzinou, K Nasreddine\u2026\u00a0- \u2026\u00a0Conference on Image and\u00a0\u2026, 2018 - Springer", "snippet": "\u2026 Underwater live fish recognition will become a necessary tool to assist marine ecologists in \nstudying the biodiversity in underwater areas because traditional techniques are destructive, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11713264068774870425&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:mT2sa5zfjaIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11713264068774870425&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Mapping tree species composition using OHS-1 hyperspectral data and deep learning algorithms in Changbai mountains, Northeast China", "title_link": "https://www.mdpi.com/537574", "publication_info": "Y Xi, C Ren, Z Wang, S Wei, J Bai, B Zhang, H Xiang\u2026\u00a0- Forests, 2019 - mdpi.com", "snippet": "\u2026 The number and type of tree species in a forest stand are also related to ecosystem parameters \nlike biodiversity and habitat quality and are, therefore, important indicators for describing \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7461768746120264150&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:1jmc9COHjWcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7461768746120264150&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] ORCA-SPOT: An automatic killer whale sound detection toolkit using deep learning", "title_link": "https://www.nature.com/articles/s41598-019-47335-w", "publication_info": "C Bergler, H Schr\u00f6ter, RX Cheng, V Barth, M Weber\u2026\u00a0- Scientific reports, 2019 - nature.com", "snippet": "\u2026 Moreover, traditional machine-learning algorithms often perform worse than modern deep \nlearning \u2026 This study utilizes a large amount of labeled data and state-of-the-art deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7021340705485197771&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:y5FvxSvQcGEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=7021340705485197771&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A novel deep learning framework approach for natural calamities detection", "title_link": "https://link.springer.com/chapter/10.1007/978-981-13-0586-3_55", "publication_info": "R Nijhawan, M Rishi, A Tiwari, R Dua\u00a0- Information and Communication\u00a0\u2026, 2019 - Springer", "snippet": "\u2026 In order to acquire an appreciable accuracy via deep learning, we provided a substantial \ndataset to our model. Because of the unavailability of an open-source dataset for natural \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6415577241302981114&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:-tnxgIK1CFkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6415577241302981114&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Mapping agricultural plastic greenhouses using Google Earth images and deep learning", "title_link": "https://www.sciencedirect.com/science/article/pii/S016816992100569X", "publication_info": "W Chen, Y Xu, Z Zhang, L Yang, X Pan, Z Jia\u00a0- Computers and Electronics\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 In this study, a deep learning method is adopted to map the distribution of APGs in \u2026 This \nresearch shows that the deep learning method can extract greenhouse information quickly and \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15504783378646911631&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:j0qhw1UOLNcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15504783378646911631&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Computer vision with deep learning for plant phenotyping in agriculture: A survey", "title_link": "https://arxiv.org/abs/2006.11391", "publication_info": "AL Chandra, SV Desai, W Guo\u2026\u00a0- arXiv preprint arXiv\u00a0\u2026, 2020 - arxiv.org", "snippet": "\u2026 deep learning based plant phenotyping. We believe that the expressive power and robustness \nof deep learning \u2026 the advancements in the field of deep learning based plant phenotyping, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=887377996513634735&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:r2mxF5aZUAwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=887377996513634735&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Benchmarking anchor-based and anchor-free state-of-the-art deep learning methods for individual tree detection in rgb high-resolution images", "title_link": "https://www.mdpi.com/1164320", "publication_info": "P Zamboni, JM Junior, JA Silva, GT Miyoshi\u2026\u00a0- Remote Sensing, 2021 - mdpi.com", "snippet": "\u2026 -free state-of-the-art deep-learning methods. We used two orthoimages divided into 220 \nnon-\u2026 Our findings contribute to a better understanding of the performance of novel deep-learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15525127264026904502&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:tkcOsf1UdNcJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15525127264026904502&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep Learning in Hyperspectral Image Reconstruction from Single RGB images\u2014A Case Study on Tomato Quality Parameters", "title_link": "https://www.mdpi.com/849358", "publication_info": "J Zhao, D Kechasov, B Rewald, G Bodner, M Verheul\u2026\u00a0- Remote Sensing, 2020 - mdpi.com", "snippet": "\u2026 In this study, we demonstrate the use of a permutation test to select an appropriate state-of-the-art \ndeep learning model for hyperspectral image reconstruction from a single RGB image. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6676839101916797719&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=r5XLI2QAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=6676839101916797719&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] An integration of deep learning with feature embedding for protein\u2013protein interaction prediction", "title_link": "https://peerj.com/articles/7126/", "publication_info": "Y Yao, X Du, Y Diao, H Zhu\u00a0- PeerJ, 2019 - peerj.com", "snippet": "\u2026 deep learning model. Combining effective feature embedding with powerful deep learning \n\u2026 a novel residue representation method and a deep learning classification framework in an \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8720402985266403403&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:S1gP-08YBXkJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8720402985266403403&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Biodiversity information retrieval through large scale content-based identification: a long-term evaluation", "title_link": "https://link.springer.com/chapter/10.1007/978-3-030-22948-1_16", "publication_info": "A Joly, H Go\u00ebau, H Glotin, C Spampinato\u2026\u00a0- \u2026\u00a0Retrieval Evaluation in\u00a0\u2026, 2019 - Springer", "snippet": "\u2026 2014b) and it is still attracting much research today, in particular on deep learning \u2026 production, \nsharing and identification of multimedia biodiversity records have increased in recent years\u2026", "cited_by": "https://scholar.google.com/scholar?cites=5485906443863225954&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=Xc2rx8j4O7UC&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=5485906443863225954&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep Learning-based Automatic Bird Species Identification from Isolated Recordings", "title_link": "https://ieeexplore.ieee.org/abstract/document/9528234/", "publication_info": "A Noumida, R Rajan\u00a0- 2021 8th International Conference on\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 ) approach using various deep learning architectures, namely \u2026 in a variety of deep learning \napplications. The performance \u2026 and necessary for avian biodiversity conservation, and it aids \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15032153784326737791&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:f8_WGznwnNAJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "GPU-based training of autoencoders for bird sound data processing", "title_link": "https://ieeexplore.ieee.org/abstract/document/7991037/", "publication_info": "J Guo, K Qian, B Schuller\u2026\u00a0- 2017 IEEE International\u00a0\u2026, 2017 - ieeexplore.ieee.org", "snippet": "\u2026 state-of-the-art deep learning methods to mining such large amount \u2026 climate changes, and \nbiodiversity of a reserve by ecologists [\u2026 highly active areas of \u2018deep learning\u2019, can contribute by \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10379678959427893039&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:L7dLCwUHDJAJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10379678959427893039&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Mining transition rules of cellular automata for simulating urban expansion by using the deep learning techniques", "title_link": "https://www.tandfonline.com/doi/abs/10.1080/13658816.2018.1480783", "publication_info": "J He, X Li, Y Yao, Y Hong, Z Jinbao\u00a0- International Journal of\u00a0\u2026, 2018 - Taylor & Francis", "snippet": "\u2026 In this paper, we used an effective deep learning method, named convolution neural network \nfor united mining (UMCNN), to solve the problem. UMCNN has substantial potential to get \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17776296894444028956&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=kqsWz5MAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=17776296894444028956&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Monitoring the Mangrove Species in Hong Kong with High Resolution Images Using Deep Learning Networks", "title_link": "https://search.proquest.com/openview/831884a0beebed5d228617a09b1ac0fc/1?pq-origsite=gscholar&cbl=2026366&diss=y", "publication_info": "L Wan - 2021 - search.proquest.com", "snippet": "\u2026 Instead of feature engineering, deep learning driven by a large amount of data is \u2026 The \nresults show that the abstract features from deep learning can improve the mapping of all \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:itlQwAySj6UJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.comjavascript:void(0)", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Deep learning-based cattle vocal classification model and real-time livestock monitoring system with noise filtering", "title_link": "https://www.mdpi.com/981394", "publication_info": "DH Jung, NY Kim, SH Moon, C Jhin, HJ Kim, JS Yang\u2026\u00a0- Animals, 2021 - mdpi.com", "snippet": "\u2026 widely adopted for protecting biodiversity and conservation [22]. \u2026 A convolutional neural \nnetwork (CNN) is a deep learning \u2026 Zhu [28] applied deep learning in classifying Australian bird \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8522250265034197436&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:vIlXlnYdRXYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8522250265034197436&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Extending deep learning approaches for forest disturbance segmentation on very high\u2010resolution satellite images", "title_link": "https://zslpublications.onlinelibrary.wiley.com/doi/abs/10.1002/rse2.194", "publication_info": "DE Kislov, KA Korznikov, J Altman\u2026\u00a0- Remote Sensing in\u00a0\u2026, 2021 - Wiley Online Library", "snippet": "\u2026 networks with complex architectures and deep learning approaches. This opens new \nopportunities and perspectives for applying deep learning methods to solving various problems in \u2026", "cited_by": "https://scholar.google.com/scholar?cites=13279820170469239877&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Rezi5RVmS7gJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=13279820170469239877&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for fusion of APEX hyperspectral and full-waveform LiDAR remote sensing data for tree species mapping", "title_link": "https://ieeexplore.ieee.org/abstract/document/8529194/", "publication_info": "W Liao, F Van Coillie, L Gao, L Li, B Zhang\u2026\u00a0- IEEE\u00a0\u2026, 2018 - ieeexplore.ieee.org", "snippet": "\u2026 The main objective of this paper is to analyze deep learning \u2026 Therefore, we propose a \ntwo-stage deep learning method for \u2026 With the proposed two-stage deep learning fusion method, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9492114856083644030&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:ft4SlCvEuoMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9492114856083644030&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Analysis of almost a hundred long distance migration paths of Italian and Swiss barn swallows (Hirundo rustica) reconstructed on the basis of light level geolocators", "title_link": "https://re.public.polimi.it/handle/11311/1071353", "publication_info": "M Pancerasa, A Roberto, DW Winkler\u2026\u00a0- 10th International\u00a0\u2026, 2018 - re.public.polimi.it", "snippet": "\u2026 by deep learning,\u2022 advanced exploration of valuable information in \u2018big data\u2019by means of \nmachine learning and process modelling,\u2022 decision-informing solutions for biodiversity \u2026", "cited_by": "https://scholar.google.comjavascript:void(0)", "related_articles": "https://scholar.google.comhttps://scholar.googleusercontent.com/scholar?q=cache:6laLfnRma8kJ:scholar.google.com/+biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "A survey of deep learning in agriculture: techniques and their applications", "title_link": "https://www.koreascience.or.kr/article/JAKO202032255805992.page", "publication_info": "C Ren, DK Kim, D Jeong\u00a0- Journal of Information Processing\u00a0\u2026, 2020 - koreascience.or.kr", "snippet": "\u2026 In this paper, we investigate 32 research contributions that apply deep learning techniques \n\u2026 of deep learning and future research topics. The survey shows that deep learning-based \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8146108821484852840&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:aNZHLtDKDHEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8146108821484852840&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Detection of financial statement fraud using deep learning for sustainable development of capital markets under information asymmetry", "title_link": "https://www.mdpi.com/1256116", "publication_info": "CL Jan\u00a0- Sustainability, 2021 - mdpi.com", "snippet": "\u2026 In this era of big data and artificial intelligence, deep learning is being applied to many \u2026 \nTwo powerful deep learning algorithms (ie, recurrent neural network (RNN) and long short-\u2026", "cited_by": "https://scholar.google.com/scholar?cites=15894523565238615360&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:QH0fRPiwlNwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15894523565238615360&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Counting fish and dolphins in sonar images using deep learning", "title_link": "https://arxiv.org/abs/2007.12808", "publication_info": "S Schneider, A Zhuang\u00a0- arXiv preprint arXiv:2007.12808, 2020 - arxiv.org", "snippet": "\u2026 Our hope is that this is just the beginning of a revolution where deep learning improves upon \nthe methods of ecological data collection and analysis. We believe that deep learning can \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9079463547118122521&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:GXYVtf27AH4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9079463547118122521&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Generating segmentation masks of herbarium specimens and a data set for training segmentation models using deep learning", "title_link": "https://bsapubs.onlinelibrary.wiley.com/doi/abs/10.1002/aps3.11352", "publication_info": "AE White, RB Dikow, M Baugh\u2026\u00a0- Applications in Plant\u00a0\u2026, 2020 - Wiley Online Library", "snippet": "\u2026 We used those images to train a U\u2010Net\u2010style deep learning model for image segmentation, \nachieving a final S\u00f8rensen\u2013Dice coefficient of 0.96. The resulting model can automatically, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=9396332146342025723&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:-9lMnk16ZoIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=9396332146342025723&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Aboveground biomass estimates of tropical mangrove forest using Sentinel-1 SAR coherence data-The superiority of deep learning over a semi-empirical\u00a0\u2026", "title_link": "https://www.sciencedirect.com/science/article/pii/S0098300421000479", "publication_info": "SM Ghosh, MD Behera\u00a0- Computers & Geosciences, 2021 - Elsevier", "snippet": "\u2026 in the Deep Learning model. However, the negligible variations in Deep Learning-based \nAGB \u2026 Interestingly, a Deep Learning algorithm could translate the exact relationship between \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5261273695579155614&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:niwa-4zMA0kJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5261273695579155614&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep Learning to Generate in Silico Chemical Property Libraries and Candidate Molecules for Small Molecule Identification in Complex Samples", "title_link": "https://pubs.acs.org/doi/abs/10.1021/acs.analchem.9b02348", "publication_info": "SM Colby, JR Nu\u00f1ez, NO Hodas, CD Corley\u2026\u00a0- Analytical\u00a0\u2026, 2019 - ACS Publications", "snippet": "\u2026 However, these deep learning applications have been \u2026 Here, we introduce a deep learning \napproach, called DarkChem\u2026 of large and complex deep learning networks without risk of \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8047958341837677492&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=98JOm8wAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=8047958341837677492&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[BOOK][B] Extracting Trait Data from Digitized Herbarium Specimens using Deep Convolutional Networks", "title_link": "https://www.researchgate.net/profile/Sohaib-Younis/publication/327987358_Extracting_Trait_Data_from_Digitized_Herbarium_Specimens_using_Deep_Convolutional_Networks/links/5bb218aca6fdccd3cb80d6c6/Extracting-Trait-Data-from-Digitized-Herbarium-Specimens-using-Deep-Convolutional-Networks.pdf", "publication_info": "S Younis, M Schmidt, C Weiland, S Dressler\u2026 - 2018 - researchgate.net", "snippet": "\u2026 trait data from digital image files by deep learning approaches.\u201d \u2026 Develop a deep learning \nframework for detection and \u2026 Deep plant phenomics: a deep learning platform for complex plant \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:ZjUYv17BfvsJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=18122134563262575974&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=18122134563262575974&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] A deep learning approach for animal breed classification-sheep", "title_link": "https://www.academia.edu/download/67333709/Paper.pdf", "publication_info": "P Dutta\u00a0- International Journal for Research in Applied Science\u00a0\u2026, 2021 - academia.edu", "snippet": "\u2026 The definition of animal genetic resources includes all activities associated with the identification, \nestimated value and quality of biodiversity and the natural environment and production \u2026", "cited_by": "https://scholar.google.com/scholar?cites=7862853494920399990&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:dkyrLZh3Hm0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Bird image retrieval and recognition using a deep learning platform", "title_link": "https://ieeexplore.ieee.org/abstract/document/8719894/", "publication_info": "YP Huang, H Basanta\u00a0- IEEE Access, 2019 - ieeexplore.ieee.org", "snippet": "\u2026 Understanding such differences between species can enhance our knowledge of exotic \nbirds as well as their ecosystems and biodiversity. However, because of observer constraints \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14133395847618473800&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:SK9HN6ToI8QJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14133395847618473800&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Real-time detection and motion recognition of human moving objects based on deep learning and multi-scale feature fusion in video", "title_link": "https://ieeexplore.ieee.org/abstract/document/8979324/", "publication_info": "M Gong, Y Shu\u00a0- IEEE Access, 2020 - ieeexplore.ieee.org", "snippet": "\u2026 recognition algorithms based on deep learning have made breakthrough progress. However, \nin some applications with high real-time requirements, the existing deep learning real-time \u2026", "cited_by": "https://scholar.google.com/scholar?cites=10287563789080669515&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Sy1TpMLExI4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=10287563789080669515&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "A deep active learning system for species identification and counting in camera trap images", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13504", "publication_info": "MS Norouzzadeh, D Morris, S Beery\u2026\u00a0- Methods in ecology\u00a0\u2026, 2021 - Wiley Online Library", "snippet": "\u2026 to dramatically increase efficiency in image-based biodiversity surveys; however, the literature \nhas \u2026 There are two major challenges for applying active deep learning on a large, high-\u2026", "cited_by": "https://scholar.google.com/scholar?cites=5874762457709343438&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:zvKQV1RZh1EJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5874762457709343438&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Automatic Pest Counting from Pheromone Trap Images Using Deep Learning Object Detectors for Matsucoccus thunbergianae Monitoring", "title_link": "https://www.mdpi.com/2075-4450/12/4/342", "publication_info": "SJ Hong, I Nam, SY Kim, E Kim, CH Lee, S Ahn\u2026\u00a0- Insects, 2021 - mdpi.com", "snippet": "\u2026 Because the counting of insects performed by humans in these pheromone traps is labor \nintensive and time consuming, this study proposes automated deep learning counting \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15093928525992423751&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:R_Hp-AVoeNEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15093928525992423751&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning methods for modelling forest biomass and structures from hyperspectral imagery", "title_link": "https://aaltodoc.aalto.fi/handle/123456789/39076", "publication_info": "P Pham - 2019 - aaltodoc.aalto.fi", "snippet": "\u2026 help us protect the environment better, reserve the biodiversity, and mitigate the hazardous \nimpacts of \u2026 This thesis directly addresses the challenge by proposing a novel deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=240199912552979628&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:rNzMPoxcVQMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=240199912552979628&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep learning for audio event detection and tagging on low-resource datasets", "title_link": "https://www.mdpi.com/328790", "publication_info": "V Morfi, D Stowell\u00a0- Applied Sciences, 2018 - mdpi.com", "snippet": "\u2026 where audio event transcription is necessary are context awareness for cars, smartphones, \netc., surveillance for dangerous events and crimes, analysis and monitoring of biodiversity, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=8775020567623145518&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Lpjs1bYix3kJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8775020567623145518&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep networks tag the location of bird vocalisations on audio spectrograms", "title_link": "https://arxiv.org/abs/1711.04347", "publication_info": "L Fanioudakis, I Potamitis\u00a0- arXiv preprint arXiv:1711.04347, 2017 - arxiv.org", "snippet": "\u2026 need to design policies on biodiversity issues. \u2026 Deep learning networks on bird audio \nrecordings was until recently sparse [17-18]. This work introduces different types of deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=911577262875856366&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:7s0J27CSpgwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=911577262875856366&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Detecting plant species in the field with deep learning and drone technology", "title_link": "https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13473", "publication_info": "K James, K Bradshaw\u00a0- Methods in Ecology and Evolution, 2020 - Wiley Online Library", "snippet": "\u2026 Deep learning has begun to be used widely in remote sensing (Zhang et al., 2016), though \napplications of particular interest in this study are the use of deep learning \u2026 that deep learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=490343425673884649&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:6XM9ab8MzgYJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=490343425673884649&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] A review on fruit recognition and feature evaluation using CNN", "title_link": "https://www.sciencedirect.com/science/article/pii/S2214785321051269", "publication_info": "D Indira, J Goddu, B Indraja, VML Challa\u2026\u00a0- Materials Today\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 In any case, deep learning has been shown as of late to be an extremely incredible \npicture identification procedure, and CNN is a best in class way to deal with deep learning. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3381922536846733898&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:SjKjCqEA7y4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "[HTML][HTML] The importance of genomic variation for biodiversity, ecosystems and people", "title_link": "https://www.nature.com/articles/s41576-020-00288-7", "publication_info": "M Stange, RDH Barrett, AP Hendry\u00a0- Nature Reviews Genetics, 2021 - nature.com", "snippet": "\u2026 on biodiversity and ecosystem services estimated that approximately 1 million species are at \nrisk of extinction. This primarily human-driven loss of biodiversity has \u2026 effects on biodiversity, \u2026", "cited_by": "https://scholar.google.com/scholar?cites=5381435243101968992&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:YFrcbteyrkoJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=5381435243101968992&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep learning approach for Sentinel-1 surface water mapping leveraging Google Earth Engine", "title_link": "https://www.sciencedirect.com/science/article/pii/S2667393221000053", "publication_info": "T Mayer, A Poortinga, B Bhandari, AP Nicolau\u2026\u00a0- ISPRS Open Journal of\u00a0\u2026, 2021 - Elsevier", "snippet": "\u2026 is adapting modern deep learning approaches. The \u2026 deep-learning algorithms at scale \nand that automatic data labeling can be an effective strategy in the development of deep-learning \u2026", "cited_by": "https://scholar.google.com/scholar?cites=18370260076144241373&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:3SoenjVG8P4J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Focus on the positives: Self-supervised learning for biodiversity monitoring", "title_link": "http://openaccess.thecvf.com/content/ICCV2021/html/Pantazis_Focus_on_the_Positives_Self-Supervised_Learning_for_Biodiversity_Monitoring_ICCV_2021_paper.html", "publication_info": "O Pantazis, GJ Brostow, KE Jones\u2026\u00a0- Proceedings of the\u00a0\u2026, 2021 - openaccess.thecvf.com", "snippet": "\u2026 For the critical task of global biodiversity monitoring, this \u2026 monly collected for the purpose of \nbiodiversity monitoring [58\u2026 biodiversity monitoring. We make the following three contributions: \u2026", "cited_by": "https://scholar.google.com/scholar?cites=14952367595591658006&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:FmpNbht7gc8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=14952367595591658006&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Deep learning emulators for groundwater contaminant transport modelling", "title_link": "https://www.sciencedirect.com/science/article/pii/S0022169420308118", "publication_info": "X Yu, T Cui, J Sreekanth, S Mangeon, R Doble, P Xin\u2026\u00a0- Journal of\u00a0\u2026, 2020 - Elsevier", "snippet": "\u2026 the feasibility of implementing deep learning emulators for a \u2026 accurate, efficient and scalable \ndeep learning emulators can be \u2026 of deep learning to emulate groundwater transport models. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17790122521961104919&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=i57NDsoAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=17790122521961104919&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Impact of deep learning-based dropout on shallow neural networks applied to stream temperature modelling", "title_link": "https://www.sciencedirect.com/science/article/pii/S0012825219305549", "publication_info": "AP Piotrowski, JJ Napiorkowski, AE Piotrowska\u00a0- Earth-Science Reviews, 2020 - Elsevier", "snippet": "\u2026 Although deep learning applicability in various fields of earth \u2026 techniques developed for \ndeep learning may help improve \u2026 features that made deep learning networks successful. In this \u2026", "cited_by": "https://scholar.google.com/scholar?cites=6052393006206081101&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:Tdj4R19r_lMJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=6052393006206081101&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] What's That Plant? WTPlant is a Deep Learning System to Identify Plants in Natural Images", "title_link": "https://www.researchgate.net/profile/Jonas-Krause-2/publication/328495056_What's_That_Plant_WTPlant_is_a_Deep_Learning_System_to_Identify_Plants_in_Natural_Images/links/5bd1380645851537f598fb11/Whats-That-Plant-WTPlant-is-a-Deep-Learning-System-to-Identify-Plants-in-Natural-Images.pdf", "publication_info": "L Lim, G Sugita - 2018 - researchgate.net", "snippet": "\u2026 Knowledge of plant species is essential to protect the biodiversity of any flora. Traditionally, \n\u2026 not only in the preservation of ecosystem biodiversity including public education, but also in \u2026", "cited_by": "https://scholar.google.com/scholar?q=related:iSwSD1nbcHgJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "related_articles": "https://scholar.google.com/scholar?cluster=8678677657494367369&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=8678677657494367369&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] TOXIFY: a deep learning approach to classify animal venom proteins", "title_link": "https://peerj.com/articles/7200/", "publication_info": "TJ Cole, MS Brewer\u00a0- PeerJ, 2019 - peerj.com", "snippet": "\u2026 Here we present toxify, a deep-learning approach to distinguish animal venom proteins from \nnon-toxic proteins by training neural networks on protein sequences encoded as numerical \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2070477216289911759&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:z_N_8A7QuxwJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2070477216289911759&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Use of deep learning for structural analysis of computer tomography images of soil samples", "title_link": "https://royalsocietypublishing.org/doi/abs/10.1098/rsos.201275", "publication_info": "R Wieland, C Ukawa, M Joschko\u2026\u00a0- Royal Society\u00a0\u2026, 2021 - royalsocietypublishing.org", "snippet": "\u2026 deep learning [6] promise new ways of analysing CT images. However, it is not known currently \nto what extent deep learning \u2026 A key challenge for the use of deep learning is annotation. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2886516510905683155&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:00zVJnn3DigJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2886516510905683155&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Automatic Snake Classification using Deep Learning Algorithm.", "title_link": "http://ceur-ws.org/Vol-2936/paper-135.pdf", "publication_info": "L Kalinathan, P Balasundaram, P Ganesh\u2026\u00a0- CLEF (Working\u00a0\u2026, 2021 - ceur-ws.org", "snippet": "\u2026 with a relatively larger dataset using newer deep learning architecture ResNeXt50-V2. An \n\u2026 species identification is an important goal for biodiversity, conservation, and global health. \u2026", "cited_by": "https://scholar.google.com/scholar?cites=350872000323891787&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:S7LvrDmM3gQJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Fine-grained image analysis with deep learning: A survey", "title_link": "https://ieeexplore.ieee.org/abstract/document/9609630/", "publication_info": "XS Wei, YZ Song, O Mac Aodha, J Wu\u2026\u00a0- \u2026\u00a0on Pattern Analysis\u00a0\u2026, 2021 - ieeexplore.ieee.org", "snippet": "\u2026 in both industry and research, with examples including automatic biodiversity monitoring [1], \n[2], [3], \u2026 Deep learning [14] in particular has emerged as a powerful method for discriminative \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11040962350082273274&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=0JRtCV4AAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=11040962350082273274&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Improved deep learning-based approach for real-time plant species recognition on the farm", "title_link": "https://ieeexplore.ieee.org/abstract/document/9249558/", "publication_info": "CL Chang, SC Chung\u00a0- 2020 12th International Symposium on\u00a0\u2026, 2020 - ieeexplore.ieee.org", "snippet": "\u2026 Biodiversity cultivation is a \"diversifiable risk\" management \u2026 Recently, deep learning \ntechnology is based on neural \u2026 affects the recognition performance of deep learning. Therefore, if \u2026", "cited_by": "https://scholar.google.com/scholar?cites=3263798893775584119&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:d3vOMc1XSy0J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.comNone"}, {"title": "Monitoring the impact of wildfires on tree species with deep learning", "title_link": "https://arxiv.org/abs/2011.02514", "publication_info": "W Zhou, L Klein\u00a0- arXiv preprint arXiv:2011.02514, 2020 - arxiv.org", "snippet": "\u2026 Here we propose a deep learning based classification method to monitor the impact of \nwildfires on tree species. Large-scale image classification on multispectral images to detect tree \u2026", "cited_by": "https://scholar.google.com/scholar?cites=11665134408153274530&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:opgpj_Dh4qEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=11665134408153274530&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Analysis of transfer learning for deep neural network based plant classification models", "title_link": "https://www.sciencedirect.com/science/article/pii/S0168169918315308", "publication_info": "A Kaya, AS Keceli, C Catal, HY Yalic, H Temucin\u2026\u00a0- \u2026\u00a0and electronics in\u00a0\u2026, 2019 - Elsevier", "snippet": "\u2026 Plant species classification is crucial for biodiversity protection and conservation. Manual \u2026 \nWe focused on deep learning models instead of traditional machine learning models \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15929778631118955947&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/citations?user=6Zgc0qEAAAAJ&hl=en&oi=sra", "all_article_versions": "https://scholar.google.com/scholar?cluster=15929778631118955947&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Towards the acoustic monitoring of birds migrating at night", "title_link": "https://biss.pensoft.net/article/36589/download/pdf/", "publication_info": "H Pamula, A Pocha, M Klaczynski\u00a0- Biodiversity Information Science\u00a0\u2026, 2019 - biss.pensoft.net", "snippet": "\u2026 The results obtained by the deep learning methods are promising (AUC exceeding 80%), \nbut higher bird detection accuracy is still needed. For a chosen bird species \u2013 Song thrush ( \u2026", "cited_by": "https://scholar.google.com/scholar?cites=15158668847282468355&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:AzYNpgBpXtIJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=15158668847282468355&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[PDF][PDF] Application of deep learning of multi-temporal Sentinel-1 images for the classification of coastal vegetation zone of the danube delta", "title_link": "https://www.researchgate.net/profile/Simona-Niculescu/publication/324979382_APPLICATION_OF_DEEP_LEARNING_OF_MULTI-TEMPORAL_SENTINEL-1_IMAGES_FOR_THE_CLASSIFICATION_OF_COASTAL_VEGETATION_ZONE_OF_THE_DANUBE_DELTA/links/5af388550f7e9b026bcc6b1a/APPLICATION-OF-DEEP-LEARNING-OF-MULTI-TEMPORAL-SENTINEL-1-IMAGES-FOR-THE-CLASSIFICATION-OF-COASTAL-VEGETATION-ZONE-OF-THE-DANUBE-DELTA.pdf", "publication_info": "S Niculescu, D Ienco, J Hanganu\u00a0- Int. Arch. Photogramm. Remote\u00a0\u2026, 2018 - researchgate.net", "snippet": "\u2026 The spatial approach relies on new spatial analysis technologies and methodologies: \nDeep Learning of multi-temporal Sentinel-1. We propose a deep learning network for image \u2026", "cited_by": "https://scholar.google.com/scholar?cites=2409409581219062817&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:IST8nj_xbyEJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=2409409581219062817&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "[HTML][HTML] Multi-label deep learning for gene function annotation in cancer pathways", "title_link": "https://www.nature.com/articles/s41598-017-17842-9", "publication_info": "R Guan, X Wang, MQ Yang, Y Zhang, F Zhou\u2026\u00a0- Scientific reports, 2018 - nature.com", "snippet": "\u2026 Faced with the challenge of reconciling a tremendous body of biomedical literature with \nits biological referents, we deem deep learning to be one of the most promising methods for \u2026", "cited_by": "https://scholar.google.com/scholar?cites=17907338661199425255&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:5y5pnaKlg_gJ:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=17907338661199425255&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}, {"title": "Deep Learning Techniques for Koala Activity Detection.", "title_link": "https://www.isca-speech.org/archive_v0/Interspeech_2018/pdfs/1143.pdf", "publication_info": "I Himawan, M Towsey, B Law, P Roe\u00a0- INTERSPEECH, 2018 - isca-speech.org", "snippet": "\u2026 The implications of expanding urbanization in many parts of the world are affecting \nbiodiversity. In South East Queensland, for example, increasing human population density was \u2026", "cited_by": "https://scholar.google.com/scholar?cites=4607492519226690337&as_sdt=2005&sciodt=0,5&hl=en", "related_articles": "https://scholar.google.com/scholar?q=related:IcvG4Qga8T8J:scholar.google.com/&scioq=biodivers*+OR+%22genetic+diversity%22+OR+%22*omic+diversity%22+OR+%22phylogenetic+diversity%22+OR+%22population+diversity%22+OR+%22species+diversity%22+OR+%22ecosystem+diversity%22+OR+%22functional+diversity%22+OR+%22microbial+diversity%22+OR+%22soil+diversity%22+AND+%22Deep+Learning%22&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021", "all_article_versions": "https://scholar.google.com/scholar?cluster=4607492519226690337&hl=en&as_sdt=0,5&as_ylo=2015&as_yhi=2021"}]