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Adversarial attack on deep learning-based dermatoscopic image recognition systems: Risk of misdiagnosis due to undetectable image perturbations
Deep learning algorithms have shown excellent performances in the field of medical image recognition, and practical applications have been made in several medical domains. Little is known about the feasibility and impact of an undetectable adversarial attacks, which can disrupt an algorithm by modif...
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| Publicado no: | Medicine (Baltimore) |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Lippincott Williams & Wilkins
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7738012/ https://ncbi.nlm.nih.gov/pubmed/33327315 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1097/MD.0000000000023568 |
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