Patch-level search on Private-Breast
55.1AccuracyPathDino-512
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| PathDino-512Pre-training domain=Histopathology Data, Architecture type=Transformer, Input resolution=5122023.11 | 55.1 | 49.1 | |
| MoCoV2-ResNet50Pre-training domain=Histopathology Data, Architecture type=CNN-based2023.11 | 51.9 | 37.5 | |
| Barlow-Twins-ResNet50Pre-training domain=Histopathology Data, Architecture type=CNN-based2023.11 | 50.8 | 37.5 | |
| SwAV-ResNet50Pre-training domain=Histopathology Data, Architecture type=CNN-based2023.11 | 50.2 | 37.5 | |
| iBOT-PathPre-training domain=Histopathology Data, Architecture type=Transformer2023.11 | 50.2 | 42.1 | |
| DinoSSLPathology-8Pre-training domain=Histopathology Data, Architecture type=Transformer, Patch size=82023.11 | 47.1 | 36.3 | |
| KimiaNetPre-training domain=Histopathology Data, Architecture type=CNN-based2023.11 | 46.8 | 37.2 | |
| PathDino-224Pre-training domain=Histopathology Data, Architecture type=Transformer, Input resolution=2242023.11 | 44.5 | 38.7 | |
| PLIPPre-training domain=Histopathology Data, Architecture type=Transformer2023.11 | 44.1 | 34.9 | |
| ConvNext-xlargePre-training domain=Natural Data, Architecture type=CNN-based2023.11 | 42.8 | 28.7 | |
| ConvNext-b-224Pre-training domain=Natural Data, Architecture type=CNN-based, Input resolution=2242023.11 | 39.7 | 28 | |
| EfficientNet-b5Pre-training domain=Natural Data, Architecture type=CNN-based2023.11 | 38.2 | 25.6 | |
| DinoV1-ViT-b16Pre-training domain=Natural Data, Architecture type=Transformer, Patch size=162023.11 | 38.1 | 27.2 | |
| HIPT-ViT-s16Pre-training domain=Histopathology Data, Architecture type=Transformer, Patch size=162023.11 | 37.8 | 25 | |
| DinoV1-ViT-s16Pre-training domain=Natural Data, Architecture type=Transformer, Patch size=162023.11 | 36.6 | 25 | |
| MuDiPath-DenseNet-101Pre-training domain=Histopathology Data, Architecture type=CNN-based2023.11 | 36.6 | 25.9 | |
| CLIP - ViT-B/16Pre-training domain=Natural Data, Architecture type=Transformer, Patch size=162023.11 | 36.4 | 26.8 | |
| BiomedCLIPPre-training domain=Histopathology Data, Architecture type=Transformer2023.11 | 34.1 | 22.7 | |
| ResNet50Pre-training domain=Natural Data, Architecture type=CNN-based2023.11 | 32.5 | 19 | |
| MuDiPath-ResNet50Pre-training domain=Histopathology Data, Architecture type=CNN-based2023.11 | 32.5 | 20.9 | |
| DinoV2-ViT-b14Pre-training domain=Natural Data, Architecture type=Transformer, Patch size=142023.11 | 31.8 | 20.9 | |
| DenseNet121Pre-training domain=Natural Data, Architecture type=CNN-based2023.11 | 31.4 | 19.2 | |
| EfficientNet-b3-288Pre-training domain=Natural Data, Architecture type=CNN-based, Input resolution=2882023.11 | 29.7 | 16.6 | |
| ViT-b16-224Pre-training domain=Natural Data, Architecture type=Transformer, Input resolution=224, Patch size=162023.11 | 29.6 | 16.7 |