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Improving Semi-supervised Deep Learning by using Automatic Thresholding
  to Deal with Out of Distribution Data for COVID-19 Detection using Chest
  X-ray Images

Improving Semi-supervised Deep Learning by using Automatic Thresholding to Deal with Out of Distribution Data for COVID-19 Detection using Chest X-ray Images

3 November 2022
Isaac Benavides-Mata
Saul Calderon-Ramirez
ArXivPDFHTML

Papers citing "Improving Semi-supervised Deep Learning by using Automatic Thresholding to Deal with Out of Distribution Data for COVID-19 Detection using Chest X-ray Images"

2 / 2 papers shown
Title
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
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,136
0
06 Jun 2015
1