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/earthLD/Algorithm
https://github.com/edreismd/convirt-pytorch
Contrastive Learning of Medical Visual Representations from Paired Images and Text
https://github.com/edureisMD/ConVIRT-pytorch
Contrastive Learning of Medical Visual Representations from Paired Images and Text
https://github.com/enzomuschik/distilfnd
https://github.com/epoc88/PFLD_68pts_Pytorch_2020
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/eric-erki/IdenProf
https://github.com/ericjang/odin
https://github.com/eshoyuan/taop2021-3rd-solution
https://github.com/espositoandrea/Detecting-Alzheimer-Using-Amiloyd-PET-Scans
https://github.com/ewinata/CIFAR-10
https://github.com/fL0n9/SKFAC-MindSpore
https://github.com/fabiofumarola/ultrayolo
https://github.com/fabxy/accessibilityCV
https://github.com/facebook/fb.resnet.torch
https://github.com/facebookarchive/fb.resnet.torch
https://github.com/facebookresearch/ClassyVision
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/facebookresearch/DomainBed
https://github.com/facebookresearch/hiera
https://github.com/facebookresearch/pycls
https://github.com/facebookresearch/stochastic_gradient_push
https://github.com/facundoq/transformational_measures_experiments
https://github.com/fastai/fastai
https://github.com/fchollet/deep-learning-models
https://github.com/federicopozzi33/MobileOne-PyTorch
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/felixgwu/img_classification_pk_pytorch
https://github.com/fengjiqiang/pretrainedmodel_pytorch
https://github.com/fengredrum/cnn-xla
https://github.com/filaPro/visda2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/filipmu/Kaggle-APTOS-2019-Blindness
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/flyyufelix/DenseNet-Keras
https://github.com/frankkramer-lab/aucmedi
Standardized Medical Image Classification across Medical Disciplines
https://github.com/fupiao1998/res2net-keras
https://github.com/fxfviolet/Densenet_for_quiz_classification
https://github.com/gaetandi/cheXpert
https://github.com/gargarchit/60DaysOfUdacity
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.