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Breast Tumour Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/UnofficialJuliaMirror/DeepMark-deepmark
https://github.com/UnofficialJuliaMirrorSnapshots/DeepMark-deepmark
https://github.com/Vamshi399/CarND-Vehicle-Detection
https://github.com/VamsiKrishna1211/gender_age-detection
https://github.com/VhalPurohit/290s
https://github.com/VinayBN8997/CIFAR-10-object-detection
https://github.com/VinayBN8997/ResNet-CIFAR10
https://github.com/ViswanathaReddyGajjala/EfficientNet-RetinaNet
https://github.com/Yeeun-Lee/parrot_proj1
https://github.com/Yeeun-Lee/parrot_vision_competition
https://github.com/YerevaNN/DIIN-in-Keras
https://github.com/YixuanLi/densenet-tensorflow
https://github.com/YudeWang/UNet-Satellite-Image-Segmentation
https://github.com/Zachdr1/CNNs
https://github.com/abaietto/neural_ode_classification
https://github.com/abuchin/resnet_sign
https://github.com/aby2s/sharpmask
https://github.com/adambielski/pytorch-gconv-experiments
https://github.com/adldotori/ResNet
https://github.com/agassi4013/Log-DenseNet-Tensorflow
https://github.com/aimbsg/EVA4_S15
https://github.com/ajaystar8/PDRUNet-PyTorch
https://github.com/ajithvallabai/getsetgo_keras-beginner
https://github.com/akamaster/pytorch_resnet_cifar10
https://github.com/akar5h/Image-Recognition-with-CNN-and-Transfer-Learning-ResNet101
https://github.com/akhadangi/EM-net
https://github.com/akommini/Spoken-Numeric-Digit-detection
https://github.com/alalagong/LEDNet
https://github.com/albarji/neurowriter
https://github.com/alecwangcq/KFAC-Pytorch
https://github.com/alex-f1tor/Image-Caption
https://github.com/alexsax/midlevel-reps
https://github.com/alexwdong/IncubatorCVProject
https://github.com/alibaba/EasyCV
https://github.com/alililia/ascend_FaceAttribute
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.