Evaluation of Model Quantization Method on Vitis-AI for Mitigating Adversarial Examples

Evaluation of Model Quantization Method on Vitis-AI for Mitigating Adversarial Examples

Adversarial examples (AEs) are typical model evasion attacks and security threats in deep neural networks (DNNs). One of the countermeasures is adversarial training (AT), and it trains DNNs by using a training dataset containing AEs to achieve robustness against AEs. On the other hand, the robustnes...

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Bibliographic Details
Main Authors: Yuta Fukuda, Kota Yoshida, Takeshi Fujino
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Adversarial examples
adversarial training
Vitis-AI
FPGA
Online Access:https://ieeexplore.ieee.org/document/10216964/

Internet

https://ieeexplore.ieee.org/document/10216964/

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