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ResearchFormerly WizWand

Patch-level search on Private-Breast

55.1AccuracyPathDino-512
28.5835.46542.3549.235Nov 14, 2023
Updated 8mo ago

Evaluation results

MethodLinks
PathDino-512Pre-training domain=Histopathology Data, Architecture type=Transformer, Input resolution=5122023.1155.149.1
MoCoV2-ResNet50Pre-training domain=Histopathology Data, Architecture type=CNN-based2023.1151.937.5
Barlow-Twins-ResNet50Pre-training domain=Histopathology Data, Architecture type=CNN-based2023.1150.837.5
SwAV-ResNet50Pre-training domain=Histopathology Data, Architecture type=CNN-based2023.1150.237.5
iBOT-PathPre-training domain=Histopathology Data, Architecture type=Transformer2023.1150.242.1
DinoSSLPathology-8Pre-training domain=Histopathology Data, Architecture type=Transformer, Patch size=82023.1147.136.3
KimiaNetPre-training domain=Histopathology Data, Architecture type=CNN-based2023.1146.837.2
PathDino-224Pre-training domain=Histopathology Data, Architecture type=Transformer, Input resolution=2242023.1144.538.7
PLIPPre-training domain=Histopathology Data, Architecture type=Transformer2023.1144.134.9
ConvNext-xlargePre-training domain=Natural Data, Architecture type=CNN-based2023.1142.828.7
ConvNext-b-224Pre-training domain=Natural Data, Architecture type=CNN-based, Input resolution=2242023.1139.728
EfficientNet-b5Pre-training domain=Natural Data, Architecture type=CNN-based2023.1138.225.6
DinoV1-ViT-b16Pre-training domain=Natural Data, Architecture type=Transformer, Patch size=162023.1138.127.2
HIPT-ViT-s16Pre-training domain=Histopathology Data, Architecture type=Transformer, Patch size=162023.1137.825
DinoV1-ViT-s16Pre-training domain=Natural Data, Architecture type=Transformer, Patch size=162023.1136.625
MuDiPath-DenseNet-101Pre-training domain=Histopathology Data, Architecture type=CNN-based2023.1136.625.9
CLIP - ViT-B/16Pre-training domain=Natural Data, Architecture type=Transformer, Patch size=162023.1136.426.8
BiomedCLIPPre-training domain=Histopathology Data, Architecture type=Transformer2023.1134.122.7
ResNet50Pre-training domain=Natural Data, Architecture type=CNN-based2023.1132.519
MuDiPath-ResNet50Pre-training domain=Histopathology Data, Architecture type=CNN-based2023.1132.520.9
DinoV2-ViT-b14Pre-training domain=Natural Data, Architecture type=Transformer, Patch size=142023.1131.820.9
DenseNet121Pre-training domain=Natural Data, Architecture type=CNN-based2023.1131.419.2
EfficientNet-b3-288Pre-training domain=Natural Data, Architecture type=CNN-based, Input resolution=2882023.1129.716.6
ViT-b16-224Pre-training domain=Natural Data, Architecture type=Transformer, Input resolution=224, Patch size=162023.1129.616.7