DiRA: Discriminative, Restorative, and Adversarial Learning for Self-supervised Medical Image Analysis

Discriminative learning, restorative learning, and adversarial learning have proven beneficial for self-supervised learning schemes in computer vision and medical imaging. Existing efforts, however, omit their synergistic effects on each other in a ternary setup, which, we envision, can sig-nificant...

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Vydané v:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) Ročník 2022; s. 20792 - 20802
Hlavní autori:	Haghighi, Fatemeh, Taher, Mohammad Reza Hosseinzadeh, Gotway, Michael B., Liang, Jianming
Médium:	Konferenčný príspevok.. Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.06.2022
Predmet:	Adversarial machine learning Annotations biological and cell microscopy; Self-& semi-& meta- & unsupervised learning Computer vision Medical Representation learning Self-supervised learning Semantics Visualization
ISSN:	1063-6919, 1063-6919
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