Image Classification on Kather
94.1AccuracyL1 KDE-XE
Evaluation Results
| Method | Links | |
|---|---|---|
| L1 KDE-XEBackbone=DenseNet-402022.10 | 94.1 | |
| XEBackbone=Wide-ResNet-28-102022.10 | 93.3 | |
| MMCEBackbone=DenseNet-402022.10 | 93 | |
| L1 KDE-XEBackbone=Wide-ResNet-28-102022.10 | 92.1 | |
| FL-53Backbone=DenseNet-402022.10 | 91.6 | |
| L1 KDE-XEBackbone=ResNet-110 (SD)2022.10 | 91.4 | |
| XEBackbone=DenseNet-402022.10 | 91.3 | |
| MMCEBackbone=ResNet-110 (SD)2022.10 | 90 | |
| MMCEBackbone=Wide-ResNet-28-102022.10 | 89.9 | |
| FL-53Backbone=ResNet-110 (SD)2022.10 | 88.5 | |
| FL-53Backbone=Wide-ResNet-28-102022.10 | 87.3 | |
| XEBackbone=ResNet-110 (SD)2022.10 | 87 | |
| MMCEBackbone=ResNet-1102022.10 | 86 | |
| L1 KDE-XEBackbone=ResNet-1102022.10 | 86 | |
| FL-53Backbone=ResNet-1102022.10 | 84.4 | |
| XEBackbone=ResNet-1102022.10 | 84 |