Attention-Based Adversarial Robust Distillation in Radio Signal Classifications for Low-Power IoT Devices-Reference-Cited by-同舟云学术

Attention-Based Adversarial Robust Distillation in Radio Signal Classifications for Low-Power IoT Devices

Author:

Zhang Lu¹^ORCID,Lambotharan Sangarapillai¹^ORCID,Zheng Gan²^ORCID,Liao Guisheng³,AsSadhan Basil⁴^ORCID,Roli Fabio⁵

Affiliation:

1. Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, U.K

2. School of Engineering, University of Warwick, Coventry, U.K

3. School of Electronic Engineering, Xidian University, Xi’an, China

4. Department of Electrical Engineering, King Saud University, Riyadh, Saudi Arabia

5. Department of Informatics, Bioengineering, Robotics, and Systems Engineering, University of Genova, Genoa, Italy

Funder

U.K. Engineering and Physical Sciences Research Council

International Scientific Partnership Programme of King Saud University

CELTIC-NEXT European Collaborative Project AIMM

UKRI Innovate U.K.

EC H2020 DAWN4IoE-Data Aware Wireless Network for Internet-of-Everything

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

Reference54 articles.

1. Adversarial examples in the physical world;kurakin;arXiv 1607 02533,2016

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