"Detection of Adversarial Attacks Using Deep Learning and Features ..."

Ángel Luis Perales Gómez et al. (2025)

> Home

Details and statistics

DOI: 10.1109/ACCESS.2024.3524996

access: open

type: Journal Article

metadata version: 2025-01-14

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/access/GomezMCC25
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/access/GomezMCC25
Ángel Luis Perales Gómez, Lorenzo Fernández Maimó, Alberto Huertas Celdrán, Félix J. García Clemente:
Detection of Adversarial Attacks Using Deep Learning and Features Extracted From Interpretability Methods in Industrial Scenarios. IEEE Access 13: 2705-2722 (2025)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.