Humans can decipher adversarial images

Convolutional Neural Networks (CNNs) have reached human-level benchmarks in classifying images, but they can be “fooled” by adversarial examples that elicit bizarre misclassifications from machines. Here, the authors show how humans can anticipate which objects CNNs will see in adversarial images....

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Detalles Bibliográficos
Autores principales: Zhenglong Zhou, Chaz Firestone
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2019
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Acceso en línea:https://doaj.org/article/11bc950f138d40c9b8eaad6a445e6db4
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