SOTAVerified

Breast Cancer Histology Image Classification

Papers

Showing 110 of 17 papers

TitleStatusHype
BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pixCode2
VGGIN-Net: Deep Transfer Network for Imbalanced Breast Cancer DatasetCode1
Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological ImagesCode1
Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers0
Rotation-Agnostic Image Representation Learning for Digital Pathology0
Deep Learning Framework for Multi-class Breast Cancer Histology Image Classification0
Hierarchical ResNeXt Models for Breast Cancer Histology Image Classification0
Regression Concept Vectors for Bidirectional Explanations in HistopathologyCode0
Two-Stage Convolutional Neural Network for Breast Cancer Histology Image ClassificationCode0
Attention-Map Augmentation for Hypercomplex Breast Cancer ClassificationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1WaveMixAccuracy (%)99.39Unverified
2Breast-NETAccuracy (%)98.11Unverified
3VGGIN-NetAccuracy (%)96.15Unverified
4EfficientNet-b21:1 Accuracy92.23Unverified
5WaveMixLite-224/10Accuracy (%)91.72Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-152Accuracy (% )83Unverified