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Between-Class Adversarial Training for Improving Adversarial Robustness of Image Classification
Deep neural networks (DNNs) have been known to be vulnerable to adversarial attacks. Adversarial training (AT) is, so far, the only method that can guarantee the robustness of DNNs to adversarial attacks. However, the robustness generalization accuracy gain of AT is still far lower than the standard...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10057388/ https://www.ncbi.nlm.nih.gov/pubmed/36991962 http://dx.doi.org/10.3390/s23063252 |