Increasing the Robustness of Image Quality Assessment Models Through Adversarial Training

Increasing the Robustness of Image Quality Assessment Models Through Adversarial Training

The adversarial robustness of image quality assessment (IQA) models to adversarial attacks is emerging as a critical issue. Adversarial training has been widely used to improve the robustness of neural networks to adversarial attacks, but little in-depth research has examined adversarial training as...

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Bibliographic Details
Main Authors: Anna Chistyakova, Anastasia Antsiferova, Maksim Khrebtov, Sergey Lavrushkin, Konstantin Arkhipenko, Dmitriy Vatolin, Denis Turdakov
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Technologies
Subjects:
adversarial robustness
adversarial training
image quality assessment
adversarial defense
Online Access:https://www.mdpi.com/2227-7080/12/11/220
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