Cargando…
Approaching Adversarial Example Classification with Chaos Theory
Adversarial examples are one of the most intriguing topics in modern deep learning. Imperceptible perturbations to the input can fool robust models. In relation to this problem, attack and defense methods are being developed almost on a daily basis. In parallel, efforts are being made to simply poin...
Autores principales: | Pedraza, Anibal, Deniz, Oscar, Bueno, Gloria |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7712112/ https://www.ncbi.nlm.nih.gov/pubmed/33286969 http://dx.doi.org/10.3390/e22111201 |
Ejemplares similares
-
Minimum Adversarial Examples
por: Du, Zhenyu, et al.
Publicado: (2022) -
Clustering Approach for Detecting Multiple Types of Adversarial Examples
por: Choi, Seok-Hwan, et al.
Publicado: (2022) -
Beware the Black-Box: On the Robustness of Recent Defenses to Adversarial Examples
por: Mahmood, Kaleel, et al.
Publicado: (2021) -
Universal adversarial examples and perturbations for quantum
classifiers
por: Gong, Weiyuan, et al.
Publicado: (2021) -
Adversarial example defense based on image reconstruction
por: Zhang, Yu(AUST), et al.
Publicado: (2021)