Boosting Adversarial Training in Safety-Critical Systems Through Boundary Data Selection-Reference-Cited by-同舟云学术

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Boosting Adversarial Training in Safety-Critical Systems Through Boundary Data Selection

Published:2023-12 Issue:12 Volume:8 Page:8350-8357
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Jia Yifan¹^ORCID,Poskitt Christopher M.²^ORCID,Zhang Peixin²^ORCID,Wang Jingyi¹^ORCID,Sun Jun²^ORCID,Chattopadhyay Sudipta³^ORCID

Affiliation:

1. Zhejiang University, Hangzhou, China

2. School of Computing and Information Systems, Singapore Management University, Singapore

3. Information System Technology and Design, Singapore University of Technology and Design, Singapore

Funder

Key R&D Program of Zhejiang

NSFC Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/10287676/10298624.pdf?arnumber=10298624

Reference32 articles.

1. Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing

2. Adversarial learning

3. Adversarial training for free!;shafahi;Proc Adv Neural Inf Process Syst,0

4. Fast is better than free: Revisiting adversarial training;wong;Proc Int Conf Learn Representations,0

5. Physical Adversarial Attack on a Robotic Arm

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