Papers with Code 아카이브
Breast Cancer Histology Image Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Classification of Breast Cancer Histopathology Images using a Modified Supervised Contrastive Learning Method
Rotation-Agnostic Image Representation Learning for Digital Pathology
Attention-Map Augmentation for Hypercomplex Breast Cancer Classification
Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers
BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix
VGGIN-Net: Deep Transfer Network for Imbalanced Breast Cancer Dataset
Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological Images
MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification
Magnification Generalization for Histopathology Image Embedding
Regression Concept Vectors for Bidirectional Explanations in Histopathology
Hierarchical ResNeXt Models for Breast Cancer Histology Image Classification
Breast cancer histology classification using Deep Residual Networks
Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification
Deep Learning Framework for Multi-class Breast Cancer Histology Image Classification
Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.