Colorectal Gland Segmentation:

5 papers with code • 1 benchmarks • 2 datasets

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Most implemented papers

Rotation equivariant vector field networks

di-marcos/RotEqNet ICCV 2017

In many computer vision tasks, we expect a particular behavior of the output with respect to rotations of the input image.

Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Images

simongraham/dsf-cnn 6 Apr 2020

Histology images are inherently symmetric under rotation, where each orientation is equally as likely to appear.

Group Equivariant Convolutional Networks

adambielski/pytorch-gconv-experiments 24 Feb 2016

We introduce Group equivariant Convolutional Neural Networks (G-CNNs), a natural generalization of convolutional neural networks that reduces sample complexity by exploiting symmetries.

Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis

tueimage/se2cnn 20 Feb 2020

This study is focused on histopathology image analysis applications for which it is desirable that the arbitrary global orientation information of the imaged tissues is not captured by the machine learning models.