Medical Image Classification on 10 Datasets Average
3.23ECEQaTS
Evaluation results
| Method | Links | |
|---|---|---|
| QaTSBackbone=ViT-B2026.06 | 3.23 | |
| QaTSBackbone=RN-502026.06 | 3.56 | |
| QaTSBackbone=DN-1212026.06 | 3.56 | |
| QaTSBackbone=ViT-S2026.06 | 3.68 | |
| FeatClipBackbone=ViT-B2026.06 | 3.91 | |
| QaTSBackbone=RN-182026.06 | 4.03 | |
| FeatClipBackbone=ViT-S2026.06 | 4.42 | |
| GCBackbone=ViT-B2026.06 | 4.96 | |
| GCBackbone=RN-502026.06 | 4.98 | |
| GCBackbone=DN-1212026.06 | 5.45 | |
| FeatClipBackbone=DN-1212026.06 | 5.46 | |
| FeatClipBackbone=RN-502026.06 | 5.54 | |
| IRBackbone=ViT-B2026.06 | 5.73 | |
| TSBackbone=ViT-B2026.06 | 5.91 | |
| GCBackbone=RN-182026.06 | 5.96 | |
| AdaTSBackbone=ViT-B2026.06 | 5.97 | |
| GCBackbone=ViT-S2026.06 | 6.06 | |
| AdaTSBackbone=RN-502026.06 | 6.38 | |
| IRBackbone=RN-502026.06 | 6.42 | |
| UncalBackbone=ViT-B2026.06 | 6.58 | |
| FeatClipBackbone=RN-182026.06 | 6.67 | |
| TSBackbone=RN-502026.06 | 6.87 | |
| AdaTSBackbone=ViT-S2026.06 | 7.12 | |
| IRBackbone=ViT-S2026.06 | 7.13 | |
| IRBackbone=DN-1212026.06 | 7.14 | |
| AdaTSBackbone=DN-1212026.06 | 7.17 | |
| TSBackbone=ViT-S2026.06 | 7.22 | |
| AdaTSBackbone=RN-182026.06 | 7.25 | |
| UncalBackbone=RN-502026.06 | 7.53 | |
| IRBackbone=RN-182026.06 | 7.53 | |
| UncalBackbone=ViT-S2026.06 | 7.78 | |
| TSBackbone=DN-1212026.06 | 9.08 | |
| TSBackbone=RN-182026.06 | 9.69 | |
| UncalBackbone=DN-1212026.06 | 10.09 | |
| UncalBackbone=RN-182026.06 | 10.64 |