Breast Cancer Histology Image Classification
Métriques
Accuracy (%)
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Accuracy (%) |
|---|---|
| which-backbone-to-use-a-resource-efficient | 99.39 |
| magnification-prior-a-self-supervised-method | - |
| magnification-invariant-medical-image | 91.72 |
| breast-net-a-lightweight-dcnn-model-for | 98.11 |
| vggin-net-deep-transfer-network-for | 96.15 |