Here you will find a lot of deep learning resources, such as papers, datasets, interesting codes,etc..
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Semantic segmentation (Natural images)
- 2017 - A Review on Deep Learning Techniques Applied to Semantic Segmentation
- 2017 - Not all pixels are equal: difficulty-aware semantic segmentation via deep layer cascade
- 2017 - The one hundred layers tiramisu: Fully convolutional densenets for semantic segmentation
- 2017 - Segnet: A deep convolutional encoder-decoder architecture for image segmentation
- 2016 - Multi-scale context aggregation by dilated convolutions
- 2016 - DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
- 2016 - Attention to scale: Scale-aware semantic image segmentation
- 2016 - Enet: A deep neural network architecture for real-time semantic segmentation
- 2015 - Fully Convolutional Networks for Semantic Segmentation
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Semantic segmentation (Medical images)
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Image classification
- 2017 - Densely connected convolutional networks
- 2017 - Inception-v4, inception-resnet and the impact of residual connections on learning
- 2016 - Wide residual networks
- 2016 - Deep Residual Learning for Image Recognition
- 2016 - Rethinking the inception architecture for computer vision
- 2015 - Spatial pyramid pooling in deep convolutional networks for visual recognition
- 2014 - Very deep convolutional networks for large-scale image recognition
- 2012 - ImageNet Classification with Deep Convolutional Neural Networks
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Object detection
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Face detection
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Action recognition (Videos)
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General
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Natural images:
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Medical images: