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Adversarial robustness in deep neural networks based on variable attributes of the stochastic ensemble model
Deep neural networks (DNNs) have been shown to be susceptible to critical vulnerabilities when attacked by adversarial samples. This has prompted the development of attack and defense strategies similar to those used in cyberspace security. The dependence of such strategies on attack and defense mec...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442534/ https://www.ncbi.nlm.nih.gov/pubmed/37614968 http://dx.doi.org/10.3389/fnbot.2023.1205370 |