HyperAIHyperAI
AccueilActualitésArticles de recherche récentsTutorielsEnsembles de donnéesWikiSOTAModèles LLMClassement GPUÉvénements
Recherche
À propos
HyperAIHyperAI

Breast Tumour Classification On Pcam

Métriques

Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
Accuracy
Paper TitleRepository
Virchow0.933Virchow: A Million-Slide Digital Pathology Foundation Model-
Steerable G-CNN (e)-Learning Steerable Filters for Rotation Equivariant CNNs-
VF-CNN (C8)-Rotation equivariant vector field networks-
ResNet-34 (e)-Deep Residual Learning for Image Recognition-
G-CNN (C4)-Group Equivariant Convolutional Networks-
DenseNet-121 (e)-Densely Connected Convolutional Networks-
G-CNN (C8)-Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis-
VF-CNN (C12)-Rotation equivariant vector field networks-
VF-CNN (C4)-Rotation equivariant vector field networks-
Steerable G-CNN (C8)-Learning Steerable Filters for Rotation Equivariant CNNs-
ResNet-50 (e)-Deep Residual Learning for Image Recognition-
p4m-DenseNet (D4)-Rotation Equivariant CNNs for Digital Pathology-
Steerable G-CNN (C8)-Learning Steerable Filters for Rotation Equivariant CNNs-
Steerable G-CNN (C12)-Learning Steerable Filters for Rotation Equivariant CNNs-
G-CNN (C12)-Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis-
DSF-CNN (C8)-Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Images-
0 of 16 row(s) selected.
Breast Tumour Classification On Pcam | SOTA | HyperAI