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Models/G-CNN (C12)

G-CNN (C12)

Reported on 6 benchmarks across 3 tasks · 1 paper

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

Medical8 results

  • Breast Tumour ClassificationonPCam
    AUC· 2020-02-20
    0.962
    best: 0.975 (DSF-CNN (C8))
    Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image AnalysisarXiv:2002.08725
  • Colorectal Gland Segmentation:onCRAG
    Dice· 2020-02-20
    0.834
    best: 0.892 (PatchCL)
    Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image AnalysisarXiv:2002.08725
  • Colorectal Gland Segmentation:onCRAG
    F1-score· 2020-02-20
    0.818
    best: 0.881 (PatchCL)
    Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image AnalysisarXiv:2002.08725
  • Colorectal Gland Segmentation:onCRAG
    Hausdorff Distance (mm)· 2020-02-20
    192.2
    best: 318.9 (VF-CNN (C4))
    Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image AnalysisarXiv:2002.08725
  • Multi-tissue Nucleus SegmentationonKumar
    Dice· 2020-02-20
    0.814
    best: 0.843 (GC-MHVN)
    Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image AnalysisarXiv:2002.08725
  • Multi-tissue Nucleus SegmentationonKumar
    Hausdorff Distance (mm)· 2020-02-20
    53.4
    best: 60 (DSF-CNN (C8))
    Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image AnalysisarXiv:2002.08725
  • Multi-tissue Nucleus SegmentationonKumar
    Dice· 2020-02-20
    0.811
    best: 0.843 (GC-MHVN)
    Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image AnalysisarXiv:2002.08725
  • Multi-tissue Nucleus SegmentationonKumar
    Hausdorff Distance (mm)· 2020-02-20
    51.9
    best: 60 (DSF-CNN (C8))
    Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image AnalysisarXiv:2002.08725