Image Classification on XJTU Meningioma 5-shot 4-way (test)
99.79AccuracyAMSF-Net
Evaluation results
| Method | Links | |
|---|---|---|
| AMSF-NetTrain shot=5-shot, Backbone=ViT-Base2026.02 | 99.79 | |
| AMSF-NetTrain shot=1-shot, Backbone=ViT-Base2026.02 | 99.72 | |
| Proto-NetTrain shot=5-shot, Backbone=ResNet-122026.02 | 99.49 | |
| FRNTrain shot=5-shot, Backbone=ResNet-122026.02 | 99.33 | |
| Bi-FRNTrain shot=5-shot, Backbone=ResNet-122026.02 | 99.24 | |
| Proto-NetTrain shot=5-shot, Backbone=ViT-Base2026.02 | 99 | |
| Bi-FRNTrain shot=5-shot, Backbone=Conv-42026.02 | 98.7 | |
| Proto-NetTrain shot=1-shot, Backbone=ViT-Base2026.02 | 98.67 | |
| C2-NetTrain shot=1-shot, Backbone=ResNet-122026.02 | 98.64 | |
| Proto-NetTrain shot=5-shot, Backbone=Conv-42026.02 | 98.43 | |
| FRNTrain shot=5-shot, Backbone=Conv-42026.02 | 98.43 | |
| Proto-NetTrain shot=1-shot, Backbone=ResNet-122026.02 | 98.25 | |
| C2-NetTrain shot=5-shot, Backbone=ResNet-122026.02 | 98.06 | |
| C2-NetTrain shot=5-shot, Backbone=Conv-42026.02 | 98.05 | |
| FRNTrain shot=1-shot, Backbone=ResNet-122026.02 | 97.86 | |
| Bi-FRNTrain shot=1-shot, Backbone=ResNet-122026.02 | 97.67 | |
| C2-NetTrain shot=1-shot, Backbone=Conv-42026.02 | 97.46 | |
| Bi-FRNTrain shot=1-shot, Backbone=Conv-42026.02 | 96.27 | |
| Proto-NetTrain shot=1-shot, Backbone=Conv-42026.02 | 94.3 | |
| FRNTrain shot=1-shot, Backbone=Conv-42026.02 | 85.22 |