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Greatest papers with code

Group Equivariant Convolutional Networks

24 Feb 2016adambielski/pytorch-gconv-experiments

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

BREAST TUMOUR CLASSIFICATION COLORECTAL GLAND SEGMENTATION: MULTI-TISSUE NUCLEUS SEGMENTATION ROTATED MNIST

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

20 Feb 2020tueimage/se2cnn

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.

BREAST TUMOUR CLASSIFICATION COLORECTAL GLAND SEGMENTATION: DATA AUGMENTATION MITOSIS DETECTION MULTI-TISSUE NUCLEUS SEGMENTATION