Medical Image Segmentation On Bkai Igh
Métriques
Average Dice
mIoU
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Average Dice | mIoU |
|---|---|---|
| tganet-text-guided-attention-for-improved | 0.9023 | 0.8409 |
| real-time-polyp-detection-localisation-and | 0.6881 | - |
| qtseg-a-query-token-based-architecture-for | - | - |
| blazeneo-blazing-fast-polyp-segmentation-and | 0.78802 | - |
| focal-unet-unet-like-focal-modulation-for | 0.8021 | - |
| neounet-towards-accurate-colon-polyp | 0.80723 | - |
| emcad-efficient-multi-scale-convolutional | 0.9296 | - |
| transresu-net-transformer-based-resu-net-for | 0.9154 | 0.8568 |
| rabit-an-efficient-transformer-using | 0.94 | 0.886 |