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Models/DA-Net

DA-Net

Reported on 18 benchmarks across 2 tasks · 1 paper

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

Medical18 results

Medical Image SegmentationonDRIVE
AUC· 2024-03-07
0.9846
best: 0.9931 (Swin-Res-Net)
DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning arXiv:2403.04158
Medical Image SegmentationonDRIVE
Accuracy· 2024-03-07
0.8082
best: 0.9712 (U-Net)
DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning arXiv:2403.04158
Medical Image SegmentationonDRIVE
F1 score· 2024-03-07
0.8193
best: 0.8322 (FSG-Net)
DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning arXiv:2403.04158
Medical Image SegmentationonDRIVE
Specificity· 2024-03-07
0.9803
best: 0.9844 (MERIT-GCASCADE)
DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning arXiv:2403.04158
Medical Image SegmentationonDRIVE
sensitivity· 2024-03-07
0.8307
best: 0.842 (FSG-Net)
DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning arXiv:2403.04158
Retinal Vessel SegmentationonDRIVE
AUC· 2024-03-07
0.9846
best: 0.9931 (Swin-Res-Net)
DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning arXiv:2403.04158
Retinal Vessel SegmentationonDRIVE
Accuracy· 2024-03-07
0.8082
best: 0.9712 (U-Net)
DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning arXiv:2403.04158
Retinal Vessel SegmentationonDRIVE
F1 score· 2024-03-07
0.8193
best: 0.8322 (FSG-Net)
DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning arXiv:2403.04158
Retinal Vessel SegmentationonDRIVE
Specificity· 2024-03-07
0.9803
best: 0.9844 (MERIT-GCASCADE)
DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning arXiv:2403.04158
Retinal Vessel SegmentationonDRIVE
sensitivity· 2024-03-07
0.8307
best: 0.842 (FSG-Net)
DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning arXiv:2403.04158
Medical Image SegmentationonSTARE
AUC
0.9924
Medical Image SegmentationonSTARE
Acc
0.9786
Medical Image SegmentationonSTARE
F1 score
0.8622
Medical Image SegmentationonSTARE
Sensitivity
0.8762
Retinal Vessel SegmentationonSTARE
AUC
0.9924
Retinal Vessel SegmentationonSTARE
Acc
0.9786
Retinal Vessel SegmentationonSTARE
F1 score
0.8622
Retinal Vessel SegmentationonSTARE
Sensitivity
0.8762