Defense Against Adversarial Attacks by Reconstructing Images
Convolutional neural networks (CNNs) are vulnerable to being deceived by adversarial examples generated by adding small, human-imperceptible perturbations to a clean image. In this paper, we propose an image reconstruction network that reconstructs an input adversarial example into a clean output im...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 30(2021) vom: 01., Seite 6117-6129 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2021
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article |
| Online verfügbar |
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