Medical Image Classification
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Medical Image Classification is a task in medical image analysis that involves classifying medical images, such as X-rays, MRI scans, and CT scans, into different categories based on the type of image or the presence of specific structures or diseases. The goal is to use computer algorithms to automatically identify and classify medical images based on their content, which can help in diagnosis, treatment planning, and disease monitoring.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/phillity/BioCapsule
https://github.com/pikkaay/efficientnet_gpu
https://github.com/pmcgrath249/DMMFODS
https://github.com/pmcgrath249/DeepCVLab
https://github.com/pmcgrath249/DeepCV_Lab
https://github.com/prakhargoyal106/MelanomaClassification
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/priyankadeybhadra/CNN-on-CIFR
https://github.com/priyavrat-misra/xrays-and-gradcam
https://github.com/pszemraj/BoulderAreaDetector
https://github.com/pudae/tensorflow-densenet
https://github.com/pyaf/DenseNet-MURA-PyTorch
https://github.com/pytorch/vision
https://github.com/pytorch/vision/blob/main/torchvision/models/densenet.py
https://github.com/qubvel/efficientnet
https://github.com/qubvel/resnet_152
https://github.com/rafaelmata357/Flower-image-classifier
https://github.com/raghakot/keras-resnet
https://github.com/rahul-t-p/ASVspoof-2019
https://github.com/rahulchaurasiya1/cautious-waddle
https://github.com/rajkumargithub/densenet.mura
https://github.com/rajneeshaggarwal/google-efficientnet
https://github.com/ravi02512/efficientdet-keras
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/realmichaelye/Skin-Lesions-Classifier-ResNet50
https://github.com/researchmm/SiamDW
https://github.com/reyvaz/pneumothorax_detection
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/reyvaz/steel-defect-segmentation
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/rickyHong/tfRecord-Caltech256-repl2
https://github.com/rishabmallick/Sign-language-live-predictor
https://github.com/rjrobben/MICLe_pytorch
Big Self-Supervised Models Advance Medical Image Classification
https://github.com/rmwkwok/product_visual_search
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/robertofranceschi/Image-classification-on-Caltech101-using-CNNs
https://github.com/rohitgr7/tvmodels
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/rtanno21609/AdaptiveNeuralTrees
https://github.com/rwightman/efficientnet-jax
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/rwightman/gen-efficientnet-pytorch
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.