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Breast Tumour Classification
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/swetak20/Deep_into_CNNs
https://github.com/swxhss/densenet_tensorflow
https://github.com/syiin/ann_cancer_detection
https://github.com/syiin/resnet_cancer_detection
https://github.com/t0930198/backup
https://github.com/tanjeffreyz/deep-residual-learning
https://github.com/taylor-914/DenseNet
https://github.com/tcheung99/ResNet_MiniProject
https://github.com/tensorflow/models
https://github.com/tensorflow/models/tree/master/research/deeplab
https://github.com/tensorflow/models/tree/master/research/slim
https://github.com/tensorpack/tensorpack
https://github.com/tensorpack/tensorpack/tree/master/examples/ResNet
https://github.com/the-super-toys/glimpse-models
https://github.com/thughost2/Padam
https://github.com/tiagoCuervo/JapaNet
https://github.com/titu1994/DenseNet
https://github.com/towhee-io/towhee
https://github.com/trachpro/arcface-tf2
https://github.com/uclaml/Padam
https://github.com/ultralytics/yolov5
https://github.com/usnistgov/image-classification-resnet50
https://github.com/usnistgov/image-regression-resnet50
https://github.com/uw-hai/limeade
https://github.com/varshaneya/Res-SE-Net
https://github.com/vayuvegula/kerasModels
https://github.com/vgangal101/resnet_models
https://github.com/vietanhdev/open-adas
https://github.com/vietdhoang/resnet-18
https://github.com/vinay-EIP/EIP-session-5-assignment
https://github.com/vineeths96/Gradient-Compression
https://github.com/vineeths96/heterogeneous-systems
https://github.com/vinod377/STN-OCR
https://github.com/vinod377/STN-OCR-Tensorflow
https://github.com/vita-epfl/rock-pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.