Breast Cancer Histology Image Classification
Métriques
Accuracy (%)
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy (%) | Paper Title | Repository |
|---|---|---|---|
| WaveMix | 99.39 | Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision | |
| EfficientNet-b2 | - | Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological Images | |
| WaveMixLite-224/10 | 91.72 | Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers | - |
| Breast-NET | 98.11 | Breast-NET: a lightweight DCNN model for breast cancer detection and grading using histological samples | |
| VGGIN-Net | 96.15 | VGGIN-Net: Deep Transfer Network for Imbalanced Breast Cancer Dataset |
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