Medical Image Segmentation on Endovis multiclass 17 (test)
0.8377Dice ScoreS2M-Net
Evaluation results
| Method | Links | |
|---|---|---|
| S2M-NetLoss=MASL2026.01 | 0.8377 | |
| S2M-NetLoss=standard Dice loss2026.01 | 0.7638 | |
| UMambaLoss=MASL2026.01 | 0.6592 | |
| DuckNetLoss=MASL2026.01 | 0.6434 | |
| SwinUNetLoss=MASL2026.01 | 0.6278 | |
| UMambaLoss=standard Dice loss2026.01 | 0.6278 | |
| TransUNetLoss=MASL2026.01 | 0.6189 | |
| DuckNetLoss=standard Dice loss2026.01 | 0.6123 | |
| U-Net++Loss=MASL2026.01 | 0.5945 | |
| SwinUNetLoss=standard Dice loss2026.01 | 0.5945 | |
| RAPUNetLoss=MASL2026.01 | 0.5912 | |
| TransUNetLoss=standard Dice loss2026.01 | 0.5867 | |
| PraNetLoss=MASL2026.01 | 0.5823 | |
| U-NetLoss=MASL2026.01 | 0.5698 | |
| U-Net++Loss=standard Dice loss2026.01 | 0.5567 | |
| RAPUNetLoss=standard Dice loss2026.01 | 0.5534 | |
| PraNetLoss=standard Dice loss2026.01 | 0.5412 | |
| U-NetLoss=standard Dice loss2026.01 | 0.5234 |