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Rotation Invariance and Extensive Data Augmentation: a strategy for the Mitosis Domain Generalization (MIDOG) Challenge
2 September 2021
Maxime W. Lafarge
V. Koelzer
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Papers citing
"Rotation Invariance and Extensive Data Augmentation: a strategy for the Mitosis Domain Generalization (MIDOG) Challenge"
5 / 5 papers shown
Title
Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Images
S. Graham
David B. A. Epstein
Nasir M. Rajpoot
65
89
0
06 Apr 2020
Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis
Maxime W. Lafarge
Erik J. Bekkers
J. Pluim
R. Duits
M. Veta
MedIm
122
75
0
20 Feb 2020
Rotation Equivariant CNNs for Digital Pathology
Bastiaan S. Veeling
J. Linmans
Jim Winkens
Taco S. Cohen
Max Welling
109
583
0
08 Jun 2018
Roto-Translation Covariant Convolutional Networks for Medical Image Analysis
Erik J. Bekkers
Maxime W. Lafarge
M. Veta
K. Eppenhof
J. Pluim
R. Duits
MedIm
65
173
0
10 Apr 2018
Improved Regularization of Convolutional Neural Networks with Cutout
Terrance Devries
Graham W. Taylor
109
3,764
0
15 Aug 2017
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