Papers with Code 아카이브

Cancer-no cancer per image classification

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 1
보존된 평가 기록: 16

Binary classification between images with biopsy-proven cancers, and images without cancer. Only one image is used for the classification.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/dpetrini/two-views-classifier

공식 코드

Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional Network

https://github.com/lishen/end2end-all-conv

공식 코드

Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography

https://github.com/aralab-unr/ga-mammograms

Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography

https://github.com/gkaposto/end2end_lishen

Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography

https://github.com/nyukat/mammography_metarepository

Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography

https://github.com/yuyuyu123456/CBIS-DDSM

Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.