Cargando…
Improving Adversarial Robustness via Attention and Adversarial Logit Pairing
Though deep neural networks have achieved the state of the art performance in visual classification, recent studies have shown that they are all vulnerable to the attack of adversarial examples. In this paper, we develop improved techniques for defending against adversarial examples. First, we propo...
| Autores principales: | , , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2022
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8829878/ https://www.ncbi.nlm.nih.gov/pubmed/35156010 http://dx.doi.org/10.3389/frai.2021.752831 |