Deeply Supervised Discriminative Learning for Adversarial Defense
Deep neural networks can easily be fooled by an adversary with minuscule perturbations added to an input image. The existing defense techniques suffer greatly under white-box attack settings, where an adversary has full knowledge of the network and can iterate several times to find strong perturbati...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 43(2021), 9 vom: 09. Sept., Seite 3154-3166
|
|---|
| 1. Verfasser: |
Mustafa, Aamir
(VerfasserIn) |
|---|
| Weitere Verfasser: |
Khan, Salman H,
Hayat, Munawar,
Goecke, Roland,
Shen, Jianbing,
Shao, Ling |
|---|
| Format: | Online-Aufsatz
|
|---|
| Sprache: | English |
|---|
| Veröffentlicht: |
2021
|
|---|
| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
|
|---|
| Schlagworte: | Journal Article |
|---|