| crack-segmentation-on-crackvision12k | UNet | #2 | mIoU: 0.60333 |
| retinal-vessel-segmentation-on-rose-1-dvc | U-Net | #2 | Dice Score: 66.05 |
| lesion-segmentation-on-university-of-waterloo-skin-cancer | U-Net | #3 | Dice score: 0.836 ±0.132 |
| colorectal-gland-segmentation-on-crag | U-Net (e) | #5 | Dice: 0.844Hausdorff Distance (mm): 196.9 |
| colorectal-gland-segmentation-on-crag | FCN8 (e) | #10 | Hausdorff Distance (mm): 199.5 |
| retinal-vessel-segmentation-on-rose-1-svc | U-Net | #5 | Dice Score: 71.16 |
| retinal-vessel-segmentation-on-rose-1-svc-dvc | U-Net | #5 | Dice Score: 70.12 |
| retinal-vessel-segmentation-on-rose-2 | U-Net | #5 | Dice Score: 65.64 |
| semantic-segmentation-on-event-based-segmentation | U-Net | #5 | mIoU: 64.7 |
| semantic-segmentation-on-fine-grained-grass-segmentation | UNet | #5 | mIoU: 48.17 |
| retinal-vessel-segmentation-on-stare | U-Net | #6 | AUC: 0.7783F1 score: 0.8373 |
| semantic-segmentation-on-bjroad | UNet | #6 | IoU: 54.88 |
| semantic-segmentation-on-skyscapes-dense | U-Net | #6 | Mean IoU: 14.15 |
| semantic-segmentation-on-urbanlf | OCR (HRNetV2-W48) | #6 | mIoU (Syn): 79.36mIoU (Real): 78.60 |
| video-polyp-segmentation-on-sun-seg-easy | UNet | #6 | S measure: 0.669mean E-measure: 0.677 |
| video-polyp-segmentation-on-sun-seg-hard | UNet | #6 | Dice: 0.542S-Measure: 0.670 |
| semantic-segmentation-on-selma | UNet | #7 | mIoU: 36.2 |
| dichotomous-image-segmentation-on-dis-te4 | UNet | #11 | max F-Measure: 0.759weighted F-measure: 0.659MAE: 0.102… |
| multi-tissue-nucleus-segmentation-on-kumar | U-Net (e) | #11 | Dice: 0.758Hausdorff Distance (mm): 47.8 |
| retinal-vessel-segmentation-on-chase-db1 | U-Net | #13 | AUC: 0.9772 |
| dichotomous-image-segmentation-on-dis-te3 | UNet | #14 | max F-Measure: 0.748weighted F-measure: 0.644MAE: 0.098HCE: 883 |
| retinal-vessel-segmentation-on-drive | U-Net | #14 | AUC: 0.9755F1 score: 0.8142 |
| video-polyp-segmentation-on-sun-seg-easy-unseen | UNet | #14 | Sensitivity: 0.420 |
| video-polyp-segmentation-on-sun-seg-hard-unseen | UNet | #14 | Sensitivity: 0.429 |
| semantic-segmentation-on-trans10k | U-Net | #15 | GFLOPs: 124.55 |
| dichotomous-image-segmentation-on-dis-vd | UNet | #16 | max F-Measure: 0.692weighted F-measure: 0.586MAE: 0.113… |
| thermal-image-segmentation-on-pst900 | UNet | #16 | mIoU: 52.8 |
| dichotomous-image-segmentation-on-dis-te2 | UNet | #17 | max F-Measure: 0.703weighted F-measure: 0.597MAE: 0.107… |
| dichotomous-image-segmentation-on-dis-te1 | UNet | #18 | max F-Measure: 0.625weighted F-measure: 0.514MAE: 0.106… |
| thermal-image-segmentation-on-mfn-dataset | UNet | #41 | mIOU: 45.1 |
| medical-image-segmentation-on-cvc-clinicdb | U-Net | #43 | mean Dice: 0.8230 |
| medical-image-segmentation-on-kvasir-seg | U-Net | #51 | mean Dice: 0.8180Average MAE: 0.055S-Measure: 0.858… |