Analyzing the Noise Robustness of Deep Neural Networks
Adversarial examples, generated by adding small but intentionally imperceptible perturbations to normal examples, can mislead deep neural networks (DNNs) to make incorrect predictions. Although much work has been done on both adversarial attack and defense, a fine-grained understanding of adversaria...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 27(2021), 7 vom: 22. Juli, Seite 3289-3304
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| 1. Verfasser: |
Cao, Kelei
(VerfasserIn) |
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| Weitere Verfasser: |
Liu, Mengchen,
Su, Hang,
Wu, Jing,
Zhu, Jun,
Liu, Shixia |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2021
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics
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| Schlagworte: | Journal Article
Research Support, Non-U.S. Gov't |
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