Understanding the Energy vs. Adversarial Robustness Trade-Off in Deep Neural Networks

Understanding the Energy vs. Adversarial Robustness Trade-Off in Deep Neural Networks

Adversarial examples, which are crafted by adding small perturbations to typical inputs in order to fool the prediction of a deep neural network (DNN), pose a threat to security-critical applications, and robustness against adversarial examples is becoming an important design factor. In this work, w...

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Bibliographic Details
Main Authors: Kyungmi Lee, Anantha P. Chandrakasan
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Open Journal of Circuits and Systems
Subjects:
Convolutional neural networks
deep neural networks
hardware acceleration of machine learning algorithms
neural networks
learning systems
Online Access:https://ieeexplore.ieee.org/document/9645046/

Internet

https://ieeexplore.ieee.org/document/9645046/

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