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Found 3 papers, 1 papers with code
Rotation-Scale Equivariant Steerable Filters
When conventional CNNs are applied to histopathology image analysis, the generalization performance of models is limited because 1) a part of the parameters of filters are trained to fit rotation transformation, thus decreasing the capability of learning other discriminative features; 2) fixed-size filters trained on images at a given scale fail to generalize to those at different scales.
Scale-Equivariant UNet for Histopathology Image Segmentation
Digital histopathology slides are scanned and viewed under different magnifications and stored as images at different resolutions.
ADS_UNet: A Nested UNet for Histopathology Image Segmentation
Nested arrangements of these encoder and decoder maps give rise to extensions of the UNet model, such as UNete and UNet++.
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