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Models/Study Group Learning

Study Group Learning

Reported on 12 benchmarks across 2 tasks · 1 paper · 10 SOTA

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

Medical12 results

  • Medical Image SegmentationonCHASE_DB1
    AUC· 2021-03-05
    0.992
    best: 0.9937 (FSG-Net)
    SOTA
    Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy LabelsarXiv:2103.03451
  • Medical Image SegmentationonCHASE_DB1
    Sensitivity· 2021-03-05
    0.869
    best: 0.8798 (FR-UNet)
    SOTA
    Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy LabelsarXiv:2103.03451
  • Medical Image SegmentationonDRIVE
    AUC· 2021-03-05
    0.9886
    best: 0.9931 (Swin-Res-Net)
    SOTA
    Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy LabelsarXiv:2103.03451
  • Medical Image SegmentationonDRIVE
    F1 score· 2021-03-05
    0.8316
    best: 0.8322 (FSG-Net)
    SOTA
    Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy LabelsarXiv:2103.03451
  • Medical Image SegmentationonDRIVE
    sensitivity· 2021-03-05
    0.838
    best: 0.842 (FSG-Net)
    SOTA
    Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy LabelsarXiv:2103.03451
  • Retinal Vessel SegmentationonCHASE_DB1
    AUC· 2021-03-05
    0.992
    best: 0.9937 (FSG-Net)
    SOTA
    Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy LabelsarXiv:2103.03451
  • Retinal Vessel SegmentationonCHASE_DB1
    Sensitivity· 2021-03-05
    0.869
    best: 0.8798 (FR-UNet)
    SOTA
    Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy LabelsarXiv:2103.03451
  • Retinal Vessel SegmentationonDRIVE
    AUC· 2021-03-05
    0.9886
    best: 0.9931 (Swin-Res-Net)
    SOTA
    Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy LabelsarXiv:2103.03451
  • Retinal Vessel SegmentationonDRIVE
    F1 score· 2021-03-05
    0.8316
    best: 0.8322 (FSG-Net)
    SOTA
    Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy LabelsarXiv:2103.03451
  • Retinal Vessel SegmentationonDRIVE
    sensitivity· 2021-03-05
    0.838
    best: 0.842 (FSG-Net)
    SOTA
    Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy LabelsarXiv:2103.03451
  • Medical Image SegmentationonCHASE_DB1
    F1 score· 2021-03-05
    0.8271
    best: 0.8957 (RV-GAN)
    Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy LabelsarXiv:2103.03451
  • Retinal Vessel SegmentationonCHASE_DB1
    F1 score· 2021-03-05
    0.8271
    best: 0.8957 (RV-GAN)
    Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy LabelsarXiv:2103.03451