This is the same one as before, but I use deep learning
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Updated
Dec 13, 2018 - Jupyter Notebook
This is the same one as before, but I use deep learning
A boring 33 class fruit classifier.
This project focuses on building and improving a fruit recognition model using convolutional neural networks (CNNs) to accurately classify various fruit types, enhancing generalization with advanced model architecture and regularization techniques.
CNN is used to build a deep learning model for the prediction of fruits. Total of 31 different fruits classes are there
Fruit Classification using CNN
An Api thats collects data from an image and returns the descriptive properties
Classification using fruits360 from kaggle, and applying ML techniques
Artificial Neural Network in Web Assembly, C++ Core & Interactive Website.
Image segmentation model for checking apple quality using UNet model architecture on TensorFlow along with AWS SageMaker deployment.
Machine Learning with Streamlit Python
This project aims to classify different types of fruits using deep learning. The objective is to build a model that can accurately identify the type of fruit based on images.
Ripeness Palm Oil with deep learning model
Predict food (Fruits and Vegetables) images using Python
Página de apresentação do projeto de frutas e vegetais
AI-Driven Smart Fruit Classifier
FruitNutritionDetector: FastAPI-based API for Fruit Detection and Nutritional Information Retrieval using ImageAI and USDA API. Detect fruits from images and fetch detailed nutritional data.
利用深度学习实现花果图像识别; Flower and fruit image recognition using deep learning
Reconnaissance des fruits en utilisant les modéles de deep learning: Resnet, Vgg16, MobileNetV2, CNN personalisé
Fruit image classifier made with Keras VGG19 transfer learning and flask.
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