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Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised
  Knee Osteoarthritis Severity Grading from Plain Radiographs

Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading from Plain Radiographs

4 March 2020
Huy Hoang Nguyen
S. Saarakkala
Matthew Blaschko
A. Tiulpin
ArXivPDFHTML

Papers citing "Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading from Plain Radiographs"

3 / 3 papers shown
Title
Improving Image Classification of Knee Radiographs: An Automated Image
  Labeling Approach
Improving Image Classification of Knee Radiographs: An Automated Image Labeling Approach
Jikai Zhang
Carlos Santos
Christine Park
Maciej Mazurowski
R. Colglazier
24
2
0
06 Sep 2023
There Are Many Consistent Explanations of Unlabeled Data: Why You Should
  Average
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average
Ben Athiwaratkun
Marc Finzi
Pavel Izmailov
A. Wilson
202
243
0
14 Jun 2018
Mean teachers are better role models: Weight-averaged consistency
  targets improve semi-supervised deep learning results
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen
Harri Valpola
OOD
MoMe
261
1,275
0
06 Mar 2017
1