Papers with Code · CC BY-SA 4.0

Breast Cancer Histology Image Classification

12 평가 기록 7 datasets

논문

Breast-NET: a lightweight DCNN model for breast cancer detection and grading using histological samples

2024-08-10 이 페이지의 평가 2건

Accuracy (%): 98.11

Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological Images

2203.07707 2022-03-15 이 페이지의 평가 2건

Accuracy (Inter-Patient): 92.151:1 Accuracy: 92.23

Breast cancer histology classification using Deep Residual Networks

2018-07-01 이 페이지의 평가 1건

Accuracy (% ): 83

Classification of Breast Tumours Based on Histopathology Images Using Deep Features and Ensemble of Gradient Boosting Methods

2209.01380 2022-09-03 이 페이지의 평가 1건

1:1 Accuracy: 96.46

Classification of Luminal Subtypes in Full Mammogram Images Using Transfer Learning

2301.09282 2023-01-23 이 페이지의 평가 1건

AUC: 0.6688

Curvature-based Feature Selection with Application in Classifying Electronic Health Records

2101.03581 2021-01-10 이 페이지의 평가 1건

Mean Accuracy: 79.17

Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers

2302.11488 2023-02-22 이 페이지의 평가 1건

Accuracy (%): 91.72

VGGIN-Net: Deep Transfer Network for Imbalanced Breast Cancer Dataset

2022-03-29 이 페이지의 평가 1건

Accuracy (%): 96.15

Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision

2406.05612 2024-06-09 이 페이지의 평가 1건

Accuracy (%): 99.39

XBNet : An Extremely Boosted Neural Network

2106.05239 2021-06-09 이 페이지의 평가 1건

Accuracy: 96.49Average Precision: 0.95