AFD: Defending Convolutional Neural Networks Without Using Adversarial Samples
The vulnerability of deep neural networks to adversarial attacks has attracted much research effort. Still, studies have shown that it is challenging to simultaneously achieve both strong robustness to adversarial attacks and low degradation in the performance on the original task, as there is alway...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Open Journal of Signal Processing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11007011/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|