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Robust Classification from Noisy Labels: Integrating Additional
  Knowledge for Chest Radiography Abnormality Assessment

Robust Classification from Noisy Labels: Integrating Additional Knowledge for Chest Radiography Abnormality Assessment

12 April 2021
Sebastian Gündel
A. Setio
Florin-Cristian Ghesu
Sasa Grbic
Bogdan Georgescu
Andreas Maier
Dorin Comaniciu
    NoLa
ArXivPDFHTML

Papers citing "Robust Classification from Noisy Labels: Integrating Additional Knowledge for Chest Radiography Abnormality Assessment"

3 / 3 papers shown
Title
SDFN: Segmentation-based Deep Fusion Network for Thoracic Disease
  Classification in Chest X-ray Images
SDFN: Segmentation-based Deep Fusion Network for Thoracic Disease Classification in Chest X-ray Images
Han Liu
Lei Wang
Y. Nan
F. Jin
Qi Wang
J. Pu
104
94
0
30 Oct 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,675
0
05 Dec 2016
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
9,145
0
06 Jun 2015
1