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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/alililia/ms_extend/tree/main/gpu_resnet
https://github.com/alisha17/benchmarks
https://github.com/alrojo/lasagne_residual_network
https://github.com/alvarobartt/serving-pytorch-models
https://github.com/aman-garg0001/fruit-classifier
https://github.com/amazon-research/long-short-term-transformer
https://github.com/amazon-science/long-short-term-transformer
https://github.com/amogh7joshi/engagement-detection
https://github.com/amogh7joshi/fer
https://github.com/amogh7joshi/plant-health-detection
https://github.com/andreasveit/densenet-pytorch
https://github.com/andrijdavid/clinical-brain-interface-2020
https://github.com/angelvillar96/FaceEmoji
https://github.com/anguyen8/sam
https://github.com/anibali/dsnt-pose2d
https://github.com/aniket-patra-1998/FLOWER_RECOGNITION
https://github.com/anjandeepsahni/face_classification
https://github.com/anjandeepsahni/face_recognition
https://github.com/ankit-vaghela30/Google-landmark-prediction
https://github.com/anoushkrit/Knowledge
https://github.com/arahosu/musicslots
https://github.com/ariangc/breinchallenge
https://github.com/arnavdodiedo/DenseNet-Fashion-MNIST
https://github.com/arnavdodiedo/DenseNet-MNIST
https://github.com/asad-62/IVP-DNN
https://github.com/ashishpatel26/BrainMRI-Segmentation-Keras
https://github.com/asprenger/keras_fc_densenet
https://github.com/astoycos/Mini_Project2
https://github.com/atapour/ransomware-classification
https://github.com/aurelien-peden/Deep-Learning-paper-implementations
https://github.com/avocardio/resnet_vs_convnext
https://github.com/axmoyal/Steganalysis-with-CNN
https://github.com/ayushpatidar/PR1-DenseNet
https://github.com/azima-fariha/DeepLearning_DenselyConnectedConvolutionalNetworks
https://github.com/b8goal/PIRL-Residual-network
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.