ME-Net: Towards effective adversarial robustness with matrix estimation
Copyright © 2019 ASME Deep neural networks are vulnerable to adversarial attacks. The literature is rich with algorithms that can easily craft successful adversarial examples. In contrast, the performance of defense techniques still lags behind. This paper proposes ME-Net, a defense method that leve...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2021
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| Online Access: | https://hdl.handle.net/1721.1/132310 |