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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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| Publié dans: | Sensors (Basel) |
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| Auteurs principaux: | , , , , , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
MDPI
2021
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8201392/ https://ncbi.nlm.nih.gov/pubmed/34200216 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s21113922 |
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