Adversarial Attack and Defence through Adversarial Training and Feature Fusion for Diabetic Retinopathy Recognition

Due to the rapid growth in artificial intelligence (AI) and deep learning (DL) approaches, the security and robustness of the deployed algorithms need to be guaranteed. The security susceptibility of the DL algorithms to adversarial examples has been widely acknowledged. The artificially created exa...

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Detalles Bibliográficos
Autores principales: Lal, Sheeba, Rehman, Saeed Ur, Shah, Jamal Hussain, Meraj, Talha, Rauf, Hafiz Tayyab, Damaševičius, Robertas, Mohammed, Mazin Abed, Abdulkareem, Karrar Hameed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201392/
https://www.ncbi.nlm.nih.gov/pubmed/34200216
http://dx.doi.org/10.3390/s21113922

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201392/
https://www.ncbi.nlm.nih.gov/pubmed/34200216
http://dx.doi.org/10.3390/s21113922

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