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Models/UACANet-S

UACANet-S

Reported on 16 benchmarks across 1 task · 1 paper · 6 SOTA

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

Medical16 results

  • Medical Image SegmentationonETIS-LARIBPOLYPDB
    Average MAE· 2021-07-06
    0.023
    best: 0.012 (UACANet-L)
    SOTA
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonCVC-ColonDB
    Average MAE· 2021-07-06
    0.034
    best: 0.026 (DuAT)
    SOTA
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonCVC-ColonDB
    S-Measure· 2021-07-06
    0.848
    best: 0.865 (Polyp-PVT)
    SOTA
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonCVC-ColonDB
    mIoU· 2021-07-06
    0.704
    best: 0.9096 (RAPUNet)
    SOTA
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonCVC-ColonDB
    max E-Measure· 2021-07-06
    0.897
    best: 0.913 (Polyp-PVT)
    SOTA
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonCVC-ColonDB
    mean Dice· 2021-07-06
    0.783
    best: 0.9526 (RAPUNet)
    SOTA
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonKvasir-SEG
    Average MAE· 2021-07-06
    0.026
    best: 0.021 (BDG-Net)
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonKvasir-SEG
    S-Measure· 2021-07-06
    0.914
    best: 0.929 (CaraNet)
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonKvasir-SEG
    mIoU· 2021-07-06
    0.852
    best: 0.9065 (EffiSegNet-B5)
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonKvasir-SEG
    max E-Measure· 2021-07-06
    0.951
    best: 0.972 (BDG-Net)
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonKvasir-SEG
    mean Dice· 2021-07-06
    0.905
    best: 0.9502 (DUCK-Net)
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonETIS-LARIBPOLYPDB
    S-Measure· 2021-07-06
    0.815
    best: 0.868 (CaraNet)
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonETIS-LARIBPOLYPDB
    mIoU· 2021-07-06
    0.615
    best: 0.9179 (RAPUNet)
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonETIS-LARIBPOLYPDB
    max E-Measure· 2021-07-06
    0.851
    best: 0.905 (UACANet-L)
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonETIS-LARIBPOLYPDB
    mean Dice· 2021-07-06
    0.694
    best: 0.9572 (RAPUNet)
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368
  • Medical Image SegmentationonCVC-ClinicDB
    mean Dice· 2021-07-06
    0.916
    best: 0.9684 (DUCK-Net)
    UACANet: Uncertainty Augmented Context Attention for Polyp SegmentationarXiv:2107.02368