U2netme

Reported on 4 benchmarks across 1 task · 1 paper · 4 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Medical4 results

Medical Image SegmentationonISIC2018
Accuracy· 2022-02-02
0.94216
best: 94.4 (MobileUNETR)
SOTA
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation arXiv:2202.00972
Medical Image SegmentationonISIC2018
Precision· 2022-02-02
0.89502
SOTA
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation arXiv:2202.00972
Medical Image SegmentationonISIC2018
Test F1-Score· 2022-02-02
0.90604
SOTA
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation arXiv:2202.00972
Medical Image SegmentationonISIC2018
mean Dice· 2022-02-02
0.905
best: 90.74 (MobileUNETR)
SOTA
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation arXiv:2202.00972