Adversarial and Random Transformations for Robust Domain Adaptation and Generalization

Adversarial and Random Transformations for Robust Domain Adaptation and Generalization

Data augmentation has been widely used to improve generalization in training deep neural networks. Recent works show that using worst-case transformations or adversarial augmentation strategies can significantly improve accuracy and robustness. However, due to the non-differentiable properties of im...

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Bibliographic Details
Main Authors: Liang Xiao, Jiaolong Xu, Dawei Zhao, Erke Shang, Qi Zhu, Bin Dai
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Sensors
Subjects:
image classification
domain adaptation
domain generalization
consistency training
spatial transformer networks
adversarial transformations
Online Access:https://www.mdpi.com/1424-8220/23/11/5273

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https://www.mdpi.com/1424-8220/23/11/5273

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