FRNet: A Feature-Rich CNN Architecture to Defend Against Adversarial Attacks
Adversarial attacks that are possible in natural images are also transferable to medical images, paralyzing the diagnostic process and threatening the robustness of underlying Convolutional Neural Network (CNN) based classifiers. In this work, we have first demonstrated the effectiveness of well-kno...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
IEEE
2024-01-01
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| coleção: | IEEE Access |
| Assuntos: | |
| Acesso em linha: | https://ieeexplore.ieee.org/document/10431780/ |
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