'
\nYou want to classify images? You're in luck!
\nCheck out these open source projects that can help you do just that. Each of them has its own strengths and weaknesses, so you'll have to figure out which one is the best for your needs.
But don't worry, we've got you covered.
\nEnjoy!
\n\n\nTutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.
\n
It uses pytorch.
\nIt has 1 python file and 2 notebooks
\n\nimage classification with CIFAR10 dataset w/ Tensorflow
\n
It uses tensorflow.
\nIt has 1 python file and 1 notebook
\n\nThe repository contains the implementation of different machine learning techniques such as classification and cluste
\n
It uses tensorflow.
\n\n\nDeep Learning workshop including image classification, face recognition, Object detection, language modelling, image This workshop provides an introduction to deep learning using the Python programming language. Topics include image classification, face recognition, object detection, and language modelling. The workshop is based on the Deep Learning in Python book by François Chollet.
\n
It uses pytorch.
\nIt has 40 python files and 6 notebooks
\n\nIn this project, we develop a pipeline to detect unmasked faces in images. This can, for example, be used to alert peopl
\n
It uses tensorflow.
\nIt has 1 notebook
\n\nExploring CNNs and model quantization on Caltech-256 dataset
\n
It uses pytorch.
\nIt has 19 python files and 18 notebooks
\n\nImplementation of Deep Neural Networks in Keras and Tensorflow to classify motor imagery tasks using EEG data
\n
It uses tensorflow.
\nIt has 1 python file and 5 notebooks
\n\nPyTorch code for our BMVC 2019 paper \"Image Classification with Hierarchical Multigraph Networks\"
\n
It uses pytorch.
\n\n\nMulti-label classification based on timm.
\n
It uses pytorch.
\nIt has 157 python files and 1 notebook
\n\nCOVID-CXNet: Diagnosing COVID-19 in Frontal Chest X-ray Images using Deep Learning. Preprint available on arXiv: http://arxiv.org/abs/2002.06906
\n
It uses tensorflow.
\nIt has 10 python files and 1 notebook
\n\nAn Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches
\n
It uses tensorflow.
\nIt has 7 python files and 2 notebooks
\n\nMulticlass image classification using Convolutional Neural Network
\n
It uses tensorflow.
\n\n\nWhat makes convnets so powerful at image classification?
\n
It uses tensorflow.
\nIt has 1 notebook
\n\nPolSAR Image Classification Based on Dilated Convolution and Pixel-Refining Mapping Network in Complex Domain. https://github.com/PROoshio/CRPM-Net
\n
It uses tensorflow.
\nIt has 7 python files
\n\nGoogle TensorFlow project for classification using images or video input.
\n
It uses tensorflow.
\nIt has 18 python files and 3 notebooks
\n\nA set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch basd on the Caltech Birds dataset.
\n
It uses pytorch.
\nIt has 44 python files and 9 notebooks
\n\nPerforming Leaf Image classification for Recognition of Plant Diseases using various types of CNN Architecture, For dDescription:This repository contains the code for performing leaf image classification for recognition of plant diseases using various types of CNN architectures.
\n
It uses pytorch.
\nIt has 2 python files
\n\nCOVID-19 is an infectious disease. The current outbreak was officially recognized as a pandemic by the World Health OThis repository contains a machine learning model for the classification of COVID-19 images. The model is based on a convolutional neural network (CNN) and was trained on a dataset of 5,000 images.
\n
It uses tensorflow.
\n\n\nSource Code of Project Image Classification with PyTorch
\n
It uses pytorch.
\n\n\nDEmoClassi stands for Demographic (age, gender, race) and Emotions (happy, sad, angry, …) Classification from face iDescription:
\n
It uses pytorch.
\nIt has 28 python files
\n\ndeep learning for image processing including classification and object-detection etc.
\n
It uses pytorch.
\nIt has 297 python files
\n\nOpenMMLab Image Classification Toolbox and Benchmark
\n
It uses pytorch.
\nIt has 61 python files
\n\nPyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet
\n
It uses pytorch.
\nIt has 60 python files
\n\nAI based multi-label girl image classification system, implemented by using TensorFlow.
\n
It uses tensorflow.
\nIt has 25 python files
\n\nImage Test Time Augmentation with PyTorch!
\n
It uses pytorch.
\nIt has 10 python files
\n\nA scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinfocement Learning.
\n
It uses pytorch.
\nIt has 45 python files
\n\nexperiments on Paper Bag of Tricks for Image Classification with Convolutional Neural Networks and other useful triThis paper bag of tricks for image classification with convolutional neural networks is a great resource for anyone looking to get started with deep learning for image classification. It includes a number of experiments on different techniques, as well as a number of useful resources.
\n
It uses pytorch.
\nIt has 15 python files
\n\nImage classification with NVIDIA TensorRT from TensorFlow models.
\n
It uses tensorflow.
\nIt has 9 python files
\n\nTensorflow based training and classification scripts for text, images, etc
\n
It uses tensorflow.
\nIt has 5 python files
\n\nQuickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, …)
\n
It uses pytorch.
\nIt has 10 python files
\n\nTensorFlow implementation of GoogLeNet and Inception for image classification.
\n
It uses tensorflow.
\n\n\nCode for 3rd place solution in Kaggle Human Protein Atlas Image Classification Challenge.
\n
It uses pytorch.
\nIt has 34 python files
\n\nPyTorch implementation of \"WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise L1 Loss\"
\n
It uses pytorch.
\nIt has 8 python files
\n\nTraining examples and results for ImageNet(ILSVRC2012)/COCO2017/VOC2007+VOC2012 datasets.Include ResNet/DarkNet/RegNeural networks.
\n
It uses pytorch.
\nIt has 86 python files
\n\nAn Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine (SVM) for Image Classi
\n
It uses tensorflow.
\nIt has 6 python files
\n\nSatellite Image Classification using semantic segmentation methods in deep learning
\n
It uses tensorflow.
\nIt has 6 python files
\n\nReady-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
\n
It uses pytorch.
\nIt has 35 python files and 3 notebooks
\n\n3D image classification using CNN (Convolutional Neural Network)
\n
It uses tensorflow.
\nIt has 2 python files
\n\nImage classification for everyone.
\n
It uses tensorflow.
\nIt has 42 python files and 2 notebooks
\n\nTwo-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification. ICIAR 2018 Grand Challenge oThis paper presents a two-stage convolutional neural network (CNN) for breast cancer histology image classification. The first stage is a feature extraction stage that uses a 3x3 convolutional layer to extract features from the input image. The second stage is a classification stage that uses a deep CNN to classify the input image into one of the six breast cancer histology types. The proposed CNN achieves a mean accuracy of 95.8% on the validation set, which is the best result reported in the literature to date.
\n
It uses pytorch.
\nIt has 8 python files
\n\nTrojanZoo provides a universal pytorch platform to conduct security researches (especially backdoor attacks/defenses)on trojan horses.
\n
It uses pytorch.
\n\n\nAlmost any Image classification problem using pytorch
\n
It uses pytorch.
\nIt has 18 python files
\n\nTraining, evaluation and testing code for image classification using TensorFlow
\n
It uses tensorflow.
\nIt has 32 python files
\n\nuse pytorch to do image classification
\n
It uses pytorch.
\nIt has 19 python files
\n\nPyTorch implementation of the model presented in \"Satellite Image Time Series Classification with Pixel-Set Encoders This repository contains a PyTorch implementation of the model presented in \"Satellite Image Time Series Classification with Pixel-Set Encoders\" by Vincent Sainteuf, Arnaud Doucet, and Yoshua Bengio.
\n
It uses pytorch.
\nIt has 11 python files
\n\nX-ray Images (Chest images) analysis and anomaly detection using Transfer learning with inception v2
\n
It uses tensorflow.
\nIt has 8 python files
\n\ncarrier of tricks for image classification tutorials using pytorch.
\n
It uses pytorch.
\nIt has 16 python files
\n\nImage classification using Tensorflow (Inception v3)
\n
It uses tensorflow.
\nIt has 5 python files
\n\nIn this project, I implemented several ensemble methods (including bagging, AdaBoost, SAMME, stacking, snapshot ensemThis article discusses ensemble methods for image classification. It covers bagging, AdaBoost, SAMME, stacking, and snapshot ensembles, and explains how each method works. The article also provides examples of how to use each method.
\n
It uses tensorflow.
\nIt has 10 python files
\n\nEEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
\n
It uses tensorflow.
\nIt has 3 python files
'
\nYou want to classify images? You're in luck!
\nCheck out these open source projects that can help you do just that. Each of them has its own strengths and weaknesses, so you'll have to figure out which one is the best for your needs.
But don't worry, we've got you covered.
\nEnjoy!
\n\n\nTutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.
\n
It uses pytorch.
\nIt has 1 python file and 2 notebooks
\n\nimage classification with CIFAR10 dataset w/ Tensorflow
\n
It uses tensorflow.
\nIt has 1 python file and 1 notebook
\n\nThe repository contains the implementation of different machine learning techniques such as classification and cluste
\n
It uses tensorflow.
\n\n\nDeep Learning workshop including image classification, face recognition, Object detection, language modelling, image This workshop provides an introduction to deep learning using the Python programming language. Topics include image classification, face recognition, object detection, and language modelling. The workshop is based on the Deep Learning in Python book by François Chollet.
\n
It uses pytorch.
\nIt has 40 python files and 6 notebooks
\n\nIn this project, we develop a pipeline to detect unmasked faces in images. This can, for example, be used to alert peopl
\n
It uses tensorflow.
\nIt has 1 notebook
\n\nExploring CNNs and model quantization on Caltech-256 dataset
\n
It uses pytorch.
\nIt has 19 python files and 18 notebooks
\n\nImplementation of Deep Neural Networks in Keras and Tensorflow to classify motor imagery tasks using EEG data
\n
It uses tensorflow.
\nIt has 1 python file and 5 notebooks
\n\nPyTorch code for our BMVC 2019 paper \"Image Classification with Hierarchical Multigraph Networks\"
\n
It uses pytorch.
\n\n\nMulti-label classification based on timm.
\n
It uses pytorch.
\nIt has 157 python files and 1 notebook
\n\nCOVID-CXNet: Diagnosing COVID-19 in Frontal Chest X-ray Images using Deep Learning. Preprint available on arXiv: http://arxiv.org/abs/2002.06906
\n
It uses tensorflow.
\nIt has 10 python files and 1 notebook
\n\nAn Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches
\n
It uses tensorflow.
\nIt has 7 python files and 2 notebooks
\n\nMulticlass image classification using Convolutional Neural Network
\n
It uses tensorflow.
\n\n\nWhat makes convnets so powerful at image classification?
\n
It uses tensorflow.
\nIt has 1 notebook
\n\nPolSAR Image Classification Based on Dilated Convolution and Pixel-Refining Mapping Network in Complex Domain. https://github.com/PROoshio/CRPM-Net
\n
It uses tensorflow.
\nIt has 7 python files
\n\nGoogle TensorFlow project for classification using images or video input.
\n
It uses tensorflow.
\nIt has 18 python files and 3 notebooks
\n\nA set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch basd on the Caltech Birds dataset.
\n
It uses pytorch.
\nIt has 44 python files and 9 notebooks
\n\nPerforming Leaf Image classification for Recognition of Plant Diseases using various types of CNN Architecture, For dDescription:This repository contains the code for performing leaf image classification for recognition of plant diseases using various types of CNN architectures.
\n
It uses pytorch.
\nIt has 2 python files
\n\nCOVID-19 is an infectious disease. The current outbreak was officially recognized as a pandemic by the World Health OThis repository contains a machine learning model for the classification of COVID-19 images. The model is based on a convolutional neural network (CNN) and was trained on a dataset of 5,000 images.
\n
It uses tensorflow.
\n\n\nSource Code of Project Image Classification with PyTorch
\n
It uses pytorch.
\n\n\nDEmoClassi stands for Demographic (age, gender, race) and Emotions (happy, sad, angry, …) Classification from face iDescription:
\n
It uses pytorch.
\nIt has 28 python files
\n\ndeep learning for image processing including classification and object-detection etc.
\n
It uses pytorch.
\nIt has 297 python files
\n\nOpenMMLab Image Classification Toolbox and Benchmark
\n
It uses pytorch.
\nIt has 61 python files
\n\nPyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet
\n
It uses pytorch.
\nIt has 60 python files
\n\nAI based multi-label girl image classification system, implemented by using TensorFlow.
\n
It uses tensorflow.
\nIt has 25 python files
\n\nImage Test Time Augmentation with PyTorch!
\n
It uses pytorch.
\nIt has 10 python files
\n\nA scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinfocement Learning.
\n
It uses pytorch.
\nIt has 45 python files
\n\nexperiments on Paper Bag of Tricks for Image Classification with Convolutional Neural Networks and other useful triThis paper bag of tricks for image classification with convolutional neural networks is a great resource for anyone looking to get started with deep learning for image classification. It includes a number of experiments on different techniques, as well as a number of useful resources.
\n
It uses pytorch.
\nIt has 15 python files
\n\nImage classification with NVIDIA TensorRT from TensorFlow models.
\n
It uses tensorflow.
\nIt has 9 python files
\n\nTensorflow based training and classification scripts for text, images, etc
\n
It uses tensorflow.
\nIt has 5 python files
\n\nQuickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, …)
\n
It uses pytorch.
\nIt has 10 python files
\n\nTensorFlow implementation of GoogLeNet and Inception for image classification.
\n
It uses tensorflow.
\n\n\nCode for 3rd place solution in Kaggle Human Protein Atlas Image Classification Challenge.
\n
It uses pytorch.
\nIt has 34 python files
\n\nPyTorch implementation of \"WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise L1 Loss\"
\n
It uses pytorch.
\nIt has 8 python files
\n\nTraining examples and results for ImageNet(ILSVRC2012)/COCO2017/VOC2007+VOC2012 datasets.Include ResNet/DarkNet/RegNeural networks.
\n
It uses pytorch.
\nIt has 86 python files
\n\nAn Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine (SVM) for Image Classi
\n
It uses tensorflow.
\nIt has 6 python files
\n\nSatellite Image Classification using semantic segmentation methods in deep learning
\n
It uses tensorflow.
\nIt has 6 python files
\n\nReady-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
\n
It uses pytorch.
\nIt has 35 python files and 3 notebooks
\n\n3D image classification using CNN (Convolutional Neural Network)
\n
It uses tensorflow.
\nIt has 2 python files
\n\nImage classification for everyone.
\n
It uses tensorflow.
\nIt has 42 python files and 2 notebooks
\n\nTwo-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification. ICIAR 2018 Grand Challenge oThis paper presents a two-stage convolutional neural network (CNN) for breast cancer histology image classification. The first stage is a feature extraction stage that uses a 3x3 convolutional layer to extract features from the input image. The second stage is a classification stage that uses a deep CNN to classify the input image into one of the six breast cancer histology types. The proposed CNN achieves a mean accuracy of 95.8% on the validation set, which is the best result reported in the literature to date.
\n
It uses pytorch.
\nIt has 8 python files
\n\nTrojanZoo provides a universal pytorch platform to conduct security researches (especially backdoor attacks/defenses)on trojan horses.
\n
It uses pytorch.
\n\n\nAlmost any Image classification problem using pytorch
\n
It uses pytorch.
\nIt has 18 python files
\n\nTraining, evaluation and testing code for image classification using TensorFlow
\n
It uses tensorflow.
\nIt has 32 python files
\n\nuse pytorch to do image classification
\n
It uses pytorch.
\nIt has 19 python files
\n\nPyTorch implementation of the model presented in \"Satellite Image Time Series Classification with Pixel-Set Encoders This repository contains a PyTorch implementation of the model presented in \"Satellite Image Time Series Classification with Pixel-Set Encoders\" by Vincent Sainteuf, Arnaud Doucet, and Yoshua Bengio.
\n
It uses pytorch.
\nIt has 11 python files
\n\nX-ray Images (Chest images) analysis and anomaly detection using Transfer learning with inception v2
\n
It uses tensorflow.
\nIt has 8 python files
\n\ncarrier of tricks for image classification tutorials using pytorch.
\n
It uses pytorch.
\nIt has 16 python files
\n\nImage classification using Tensorflow (Inception v3)
\n
It uses tensorflow.
\nIt has 5 python files
\n\nIn this project, I implemented several ensemble methods (including bagging, AdaBoost, SAMME, stacking, snapshot ensemThis article discusses ensemble methods for image classification. It covers bagging, AdaBoost, SAMME, stacking, and snapshot ensembles, and explains how each method works. The article also provides examples of how to use each method.
\n
It uses tensorflow.
\nIt has 10 python files
\n\nEEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
\n
It uses tensorflow.
\nIt has 3 python files
Hi @satoshidatamoto, wow, this is great collection. Thank you for sharing.
", "rawMarkdown": "Hi @satoshidatamoto, wow, this is great collection. Thank you for sharing.", "votes": null }, { "id": "1794839", "postDate": "05/19/2022 07:54:05", "content": "@satoshidatamoto This is a great compilation of projects
", "rawMarkdown": "satoshidatamoto This is a great compilation of projects", "votes": null } ], "comments": [ { "id": 1794625, "author_name": "balabaskar", "author_url": "", "post_date": "05/19/2022 02:53:23", "content": "Hi @satoshidatamoto, wow, this is great collection. Thank you for sharing.
", "votes": null, "replies": [] }, { "id": 1794839, "author_name": "alanjo", "author_url": "", "post_date": "05/19/2022 07:54:05", "content": "@satoshidatamoto This is a great compilation of projects
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "1794405": "'\n\nYou want to classify images? You're in luck!\nCheck out these open source projects that can help you do just that. Each of them has its own strengths and weaknesses, so you'll have to figure out which one is the best for your needs.\n\n\nBut don't worry, we've got you covered.\n\nEnjoy!\n\n\n_____\n\n#### [pytorch-image-classification](https://github.com/bentrevett/pytorch-image-classification)\n> Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.\n\nIt uses pytorch.\nIt has 1 python file and 2 notebooks\n_____\n\n\n\n#### [CIFAR10-img-classification-tensorflow](https://github.com/deep-diver/CIFAR10-img-classification-tensorflow)\n> image classification with CIFAR10 dataset w/ Tensorflow\n\nIt uses tensorflow.\nIt has 1 python file and 1 notebook\n_____\n\n\n\n#### [Hyperspectral_Image_Analysis_Simplified](https://github.com/syamkakarla98/Hyperspectral_Image_Analysis_Simplified)\n> The repository contains the implementation of different machine learning techniques such as classification and cluste\n\nIt uses tensorflow.\n\n_____\n\n\n\n#### [Deep_Learning_in_Python_2018](https://github.com/snrazavi/Deep_Learning_in_Python_2018)\n> Deep Learning workshop including image classification, face recognition, Object detection, language modelling, image This workshop provides an introduction to deep learning using the Python programming language. Topics include image classification, face recognition, object detection, and language modelling. The workshop is based on the Deep Learning in Python book by François Chollet.\n\nIt uses pytorch.\nIt has 40 python files and 6 notebooks\n_____\n\n\n\n#### [face-mask-detection](https://github.com/datarootsio/face-mask-detection)\n> In this project, we develop a pipeline to detect unmasked faces in images. This can, for example, be used to alert peopl\n\nIt uses tensorflow.\nIt has 1 notebook\n_____\n\n\n\n#### [image-classification-caltech-256](https://github.com/TropComplique/image-classification-caltech-256)\n> Exploring CNNs and model quantization on Caltech-256 dataset\n\nIt uses pytorch.\nIt has 19 python files and 18 notebooks\n_____\n\n\n\n#### [Motor-Imagery-Tasks-Classification-using-EEG-data](https://github.com/shariharan205/Motor-Imagery-Tasks-Classification-using-EEG-data)\n> Implementation of Deep Neural Networks in Keras and Tensorflow to classify motor imagery tasks using EEG data\n\nIt uses tensorflow.\nIt has 1 python file and 5 notebooks\n_____\n\n\n\n#### [bmvc_2019](https://github.com/bknyaz/bmvc_2019)\n> PyTorch code for our BMVC 2019 paper \"Image Classification with Hierarchical Multigraph Networks\"\n\nIt uses pytorch.\n\n_____\n\n\n\n#### [PyTorch-Image-Models-Multi-Label-Classification](https://github.com/yang-ruixin/PyTorch-Image-Models-Multi-Label-Classification)\n> Multi-label classification based on timm.\n\nIt uses pytorch.\nIt has 157 python files and 1 notebook\n_____\n\n\n\n#### [COVID-CXNet](https://github.com/armiro/COVID-CXNet)\n> COVID-CXNet: Diagnosing COVID-19 in Frontal Chest X-ray Images using Deep Learning. Preprint available on arXiv: http://arxiv.org/abs/2002.06906\n\nIt uses tensorflow.\nIt has 10 python files and 1 notebook\n_____\n\n\n\n#### [Transformer-in-Transformer](https://github.com/Rishit-dagli/Transformer-in-Transformer)\n> An Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches\n\nIt uses tensorflow.\nIt has 7 python files and 2 notebooks\n_____\n\n\n\n#### [Keras-MultiClass-Image-Classification](https://github.com/vijayg15/Keras-MultiClass-Image-Classification)\n> Multiclass image classification using Convolutional Neural Network\n\nIt uses tensorflow.\n\n_____\n\n\n\n#### [Understanding-deep-Convolutional-Neural-Networks-with-a-practical-use-case-in-Tensorflow-and-Keras](https://github.com/ahmedbesbes/Understanding-deep-Convolutional-Neural-Networks-with-a-practical-use-case-in-Tensorflow-and-Keras)\n> What makes convnets so powerful at image classification?\n\nIt uses tensorflow.\nIt has 1 notebook\n_____\n\n\n\n#### [CRPM-Net](https://github.com/PROoshio/CRPM-Net)\n> PolSAR Image Classification Based on Dilated Convolution and Pixel-Refining Mapping Network in Complex Domain. https://github.com/PROoshio/CRPM-Net\n\nIt uses tensorflow.\nIt has 7 python files\n_____\n\n\n\n#### [Deep-Learning-CNN-for-Image-Recognition](https://github.com/Kidel/Deep-Learning-CNN-for-Image-Recognition)\n> Google TensorFlow project for classification using images or video input.\n\nIt uses tensorflow.\nIt has 18 python files and 3 notebooks\n_____\n\n\n\n#### [caltech_birds](https://github.com/ecm200/caltech_birds)\n> A set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch basd on the Caltech Birds dataset.\n\nIt uses pytorch.\nIt has 44 python files and 9 notebooks\n_____\n\n\n\n#### [Plant_AI](https://github.com/soumyajit4419/Plant_AI)\n> Performing Leaf Image classification for Recognition of Plant Diseases using various types of CNN Architecture, For dDescription:This repository contains the code for performing leaf image classification for recognition of plant diseases using various types of CNN architectures.\n\nIt uses pytorch.\nIt has 2 python files\n_____\n\n\n\n#### [kaggle-COVID19-Classification](https://github.com/IbrahimSobh/kaggle-COVID19-Classification)\n> COVID-19 is an infectious disease. The current outbreak was officially recognized as a pandemic by the World Health OThis repository contains a machine learning model for the classification of COVID-19 images. The model is based on a convolutional neural network (CNN) and was trained on a dataset of 5,000 images.\n\nIt uses tensorflow.\n\n_____\n\n\n\n#### [Image-Classification-with-PyTorch](https://github.com/rowhitswami/Image-Classification-with-PyTorch)\n> Source Code of Project Image Classification with PyTorch\n\nIt uses pytorch.\n\n_____\n\n\n\n#### [DEmoClassi](https://github.com/AlkaSaliss/DEmoClassi)\n> DEmoClassi stands for Demographic (age, gender, race) and Emotions (happy, sad, angry, ...) Classification from face iDescription:\n\nIt uses pytorch.\nIt has 28 python files\n_____\n\n\n\n#### [deep-learning-for-image-processing](https://github.com/WZMIAOMIAO/deep-learning-for-image-processing)\n> deep learning for image processing including classification and object-detection etc.\n\nIt uses pytorch.\nIt has 297 python files\n_____\n\n\n\n#### [mmclassification](https://github.com/open-mmlab/mmclassification)\n> OpenMMLab Image Classification Toolbox and Benchmark\n\nIt uses pytorch.\nIt has 61 python files\n_____\n\n\n\n#### [pytorch_image_classification](https://github.com/hysts/pytorch_image_classification)\n> PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet\n\nIt uses pytorch.\nIt has 60 python files\n_____\n\n\n\n#### [DeepDanbooru](https://github.com/KichangKim/DeepDanbooru)\n> AI based multi-label girl image classification system, implemented by using TensorFlow.\n\nIt uses tensorflow.\nIt has 25 python files\n_____\n\n\n\n#### [ttach](https://github.com/qubvel/ttach)\n> Image Test Time Augmentation with PyTorch!\n\nIt uses pytorch.\nIt has 10 python files\n_____\n\n\n\n#### [Pytorch-Project-Template](https://github.com/moemen95/Pytorch-Project-Template)\n> A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinfocement Learning.\n\nIt uses pytorch.\nIt has 45 python files\n_____\n\n\n\n#### [Bag_of_Tricks_for_Image_Classification_with_Convolutional_Neural_Networks](https://github.com/weiaicunzai/Bag_of_Tricks_for_Image_Classification_with_Convolutional_Neural_Networks)\n> experiments on Paper Bag of Tricks for Image Classification with Convolutional Neural Networks and other useful triThis paper bag of tricks for image classification with convolutional neural networks is a great resource for anyone looking to get started with deep learning for image classification. It includes a number of experiments on different techniques, as well as a number of useful resources.\n\nIt uses pytorch.\nIt has 15 python files\n_____\n\n\n\n#### [tf_to_trt_image_classification](https://github.com/NVIDIA-AI-IOT/tf_to_trt_image_classification)\n> Image classification with NVIDIA TensorRT from TensorFlow models.\n\nIt uses tensorflow.\nIt has 9 python files\n_____\n\n\n\n#### [tfClassifier](https://github.com/sourcedexter/tfClassifier)\n> Tensorflow based training and classification scripts for text, images, etc\n\nIt uses tensorflow.\nIt has 5 python files\n_____\n\n\n\n#### [img_classification_pk_pytorch](https://github.com/felixgwu/img_classification_pk_pytorch)\n> Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)\n\nIt uses pytorch.\nIt has 10 python files\n_____\n\n\n\n#### [GoogLeNet-Inception](https://github.com/conan7882/GoogLeNet-Inception)\n> TensorFlow implementation of GoogLeNet and Inception for image classification.\n\nIt uses tensorflow.\n\n_____\n\n\n\n#### [kaggle-hpa](https://github.com/pudae/kaggle-hpa)\n> Code for 3rd place solution in Kaggle Human Protein Atlas Image Classification Challenge.\n\nIt uses pytorch.\nIt has 34 python files\n_____\n\n\n\n#### [wildcat.pytorch](https://github.com/durandtibo/wildcat.pytorch)\n> PyTorch implementation of \"WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise L1 Loss\"\n\nIt uses pytorch.\nIt has 8 python files\n_____\n\n\n\n#### [simpleAICV-pytorch-ImageNet-COCO-training](https://github.com/zgcr/simpleAICV-pytorch-ImageNet-COCO-training)\n> Training examples and results for ImageNet(ILSVRC2012)/COCO2017/VOC2007+VOC2012 datasets.Include ResNet/DarkNet/RegNeural networks.\n\nIt uses pytorch.\nIt has 86 python files\n_____\n\n\n\n#### [cnn-svm](https://github.com/AFAgarap/cnn-svm)\n> An Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine (SVM) for Image Classi\n\nIt uses tensorflow.\nIt has 6 python files\n_____\n\n\n\n#### [eye-in-the-sky](https://github.com/manideep2510/eye-in-the-sky)\n> Satellite Image Classification using semantic segmentation methods in deep learning\n\nIt uses tensorflow.\nIt has 6 python files\n_____\n\n\n\n#### [easy-few-shot-learning](https://github.com/sicara/easy-few-shot-learning)\n> Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.\n\nIt uses pytorch.\nIt has 35 python files and 3 notebooks\n_____\n\n\n\n#### [CNN-3D-images-Tensorflow](https://github.com/jibikbam/CNN-3D-images-Tensorflow)\n> 3D image classification using CNN (Convolutional Neural Network)\n\nIt uses tensorflow.\nIt has 2 python files\n_____\n\n\n\n#### [imageatm](https://github.com/idealo/imageatm)\n> Image classification for everyone.\n\nIt uses tensorflow.\nIt has 42 python files and 2 notebooks\n_____\n\n\n\n#### [ICIAR2018](https://github.com/ImagingLab/ICIAR2018)\n> Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification. ICIAR 2018 Grand Challenge oThis paper presents a two-stage convolutional neural network (CNN) for breast cancer histology image classification. The first stage is a feature extraction stage that uses a 3x3 convolutional layer to extract features from the input image. The second stage is a classification stage that uses a deep CNN to classify the input image into one of the six breast cancer histology types. The proposed CNN achieves a mean accuracy of 95.8% on the validation set, which is the best result reported in the literature to date.\n\nIt uses pytorch.\nIt has 8 python files\n_____\n\n\n\n#### [trojanzoo](https://github.com/ain-soph/trojanzoo)\n> TrojanZoo provides a universal pytorch platform to conduct security researches (especially backdoor attacks/defenses)on trojan horses.\n\nIt uses pytorch.\n\n_____\n\n\n\n#### [pytorch_classifiers](https://github.com/prakashjayy/pytorch_classifiers)\n> Almost any Image classification problem using pytorch\n\nIt uses pytorch.\nIt has 18 python files\n_____\n\n\n\n#### [tf_classification](https://github.com/visipedia/tf_classification)\n> Training, evaluation and testing code for image classification using TensorFlow\n\nIt uses tensorflow.\nIt has 32 python files\n_____\n\n\n\n#### [pytorch_img_classification_for_competition](https://github.com/spytensor/pytorch_img_classification_for_competition)\n> use pytorch to do image classification\n\nIt uses pytorch.\nIt has 19 python files\n_____\n\n\n\n#### [pytorch-psetae](https://github.com/VSainteuf/pytorch-psetae)\n> PyTorch implementation of the model presented in \"Satellite Image Time Series Classification with Pixel-Set Encoders This repository contains a PyTorch implementation of the model presented in \"Satellite Image Time Series Classification with Pixel-Set Encoders\" by Vincent Sainteuf, Arnaud Doucet, and Yoshua Bengio.\n\nIt uses pytorch.\nIt has 11 python files\n_____\n\n\n\n#### [X-ray-classification](https://github.com/obendidi/X-ray-classification)\n> X-ray Images (Chest images) analysis and anomaly detection using Transfer learning with inception v2\n\nIt uses tensorflow.\nIt has 8 python files\n_____\n\n\n\n#### [carrier-of-tricks-for-classification-pytorch](https://github.com/hoya012/carrier-of-tricks-for-classification-pytorch)\n> carrier of tricks for image classification tutorials using pytorch.\n\nIt uses pytorch.\nIt has 16 python files\n_____\n\n\n\n#### [image-classify-server](https://github.com/ccd97/image-classify-server)\n> Image classification using Tensorflow (Inception v3)\n\nIt uses tensorflow.\nIt has 5 python files\n_____\n\n\n\n#### [Ensemble-Methods-for-Image-Classification](https://github.com/zhangyaqi1989/Ensemble-Methods-for-Image-Classification)\n> In this project, I implemented several ensemble methods (including bagging, AdaBoost, SAMME, stacking, snapshot ensemThis article discusses ensemble methods for image classification. It covers bagging, AdaBoost, SAMME, stacking, and snapshot ensembles, and explains how each method works. The article also provides examples of how to use each method.\n\nIt uses tensorflow.\nIt has 10 python files\n_____\n\n\n\n#### [EEG-Motor-Imagery-Classification-CNNs-TensorFlow](https://github.com/SuperBruceJia/EEG-Motor-Imagery-Classification-CNNs-TensorFlow)\n> EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow\n\nIt uses tensorflow.\nIt has 3 python files\n_____", "1794625": "Hi @satoshidatamoto, wow, this is great collection. Thank you for sharing.", "1794839": "satoshidatamoto This is a great compilation of projects" }, "source": "meta" }