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Adversarial Augmentation Can Improve Adversarial Robustness Better Than Double the Labeled Data

Year: 2024

Type: article

Source: Pattern Recognition and Image Analysis

DOI: 10.1134/s1054661824701025

Authors: Nikita Lockshin, Alexander Khvostikov, Andrey Krylov

Institution: Lomonosov Moscow State University

Language: English

Topic: Adversarial Robustness in Machine Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W4409204891

FWCI:

Cites: 28

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Related to: 10