Exploring the vulnerabilities and enhancing the adversarial robustness of deep neural networks

Exploring the vulnerabilities and enhancing the adversarial robustness of deep neural networks

Deep learning, especially deep neural networks (DNNs), is at the heart of the current rise of artificial intelligence, and the major breakthroughs in the last few years have been made by DNNs. It has been demonstrated in recent works that DNNs are vulnerable to human-crafted adversarial examples, wh...

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Bibliographic Details
Main Author: Bai, Tao
Other Authors: Jun Zhao
Format: Thesis-Doctor of Philosophy
Language:English
Published: Nanyang Technological University 2022
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Online Access:https://hdl.handle.net/10356/160963

Internet

https://hdl.handle.net/10356/160963

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