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Adversarial Wear and Tear: Exploiting Natural Damage for Generating Physical-World Adversarial Examples

Fuente: arXiv

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Detalles Bibliográficos
Autores principales:	Irshad, Samra, Lee, Seungkyu, Navab, Nassir, Lee, Hong Joo, Kim, Seong Tae
Formato:	Preprint
Publicado:	2025
Materias:	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

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