Image Classification on XJTU Meningioma (4-way 1-shot, test)
0.9976AccuracyAMSF-Net
Evaluation Results
| Method | Links | |
|---|---|---|
| AMSF-NetTrain shot=5-shot, Backbone=ViT-Base2026.02 | 0.9976 | |
| AMSF-NetTrain shot=1-shot, Backbone=ViT-Base2026.02 | 0.997 | |
| Proto-NetTrain shot=5-shot, Backbone=ResNet-122026.02 | 0.9921 | |
| FRNTrain shot=5-shot, Backbone=ResNet-122026.02 | 0.9906 | |
| Bi-FRNTrain shot=1-shot, Backbone=ResNet-122026.02 | 0.985 | |
| Bi-FRNTrain shot=5-shot, Backbone=ResNet-122026.02 | 0.9847 | |
| Proto-NetTrain shot=1-shot, Backbone=ViT-Base2026.02 | 0.9817 | |
| Proto-NetTrain shot=5-shot, Backbone=ViT-Base2026.02 | 0.9787 | |
| Proto-NetTrain shot=1-shot, Backbone=ResNet-122026.02 | 0.9779 | |
| C2-NetTrain shot=1-shot, Backbone=ResNet-122026.02 | 0.977 | |
| FRNTrain shot=1-shot, Backbone=ResNet-122026.02 | 0.9735 | |
| Bi-FRNTrain shot=5-shot, Backbone=Conv-42026.02 | 0.9685 | |
| Bi-FRNTrain shot=1-shot, Backbone=Conv-42026.02 | 0.9683 | |
| C2-NetTrain shot=1-shot, Backbone=Conv-42026.02 | 0.9665 | |
| FRNTrain shot=5-shot, Backbone=Conv-42026.02 | 0.9507 | |
| C2-NetTrain shot=5-shot, Backbone=ResNet-122026.02 | 0.9489 | |
| Proto-NetTrain shot=5-shot, Backbone=Conv-42026.02 | 0.9464 | |
| C2-NetTrain shot=5-shot, Backbone=Conv-42026.02 | 0.9348 | |
| Proto-NetTrain shot=1-shot, Backbone=Conv-42026.02 | 0.8695 | |
| FRNTrain shot=1-shot, Backbone=Conv-42026.02 | 0.7892 |