DIPA: Adversarial Attack on DNNs by Dropping Information and Pixel-Level Attack on Attention
Deep neural networks (DNNs) have shown remarkable performance across a wide range of fields, including image recognition, natural language processing, and speech processing. However, recent studies indicate that DNNs are highly vulnerable to well-crafted adversarial samples, which can cause incorrec...
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| Asıl Yazarlar: | , , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
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MDPI AG
2024-07-01
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| Seri Bilgileri: | Information |
| Konular: | |
| Online Erişim: | https://www.mdpi.com/2078-2489/15/7/391 |
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