Synthetic EMG Based on Adversarial Style Transfer Can Effectively Attack Biometric-Based Personal Identification Models-Reference-Cited by-同舟云学术

Synthetic EMG Based on Adversarial Style Transfer Can Effectively Attack Biometric-Based Personal Identification Models

Published:2023 Issue: Volume:31 Page:3275-3284
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Kang Peiqi¹^ORCID,Jiang Shuo²^ORCID,Shull Peter B.¹^ORCID

Affiliation:

1. State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China

2. College of Electronics and Information Engineering, Tongji University, Shanghai, China

Funder

National Natural Science Foundation of China

Shanghai Municipal Science and Technology Major Project

Chenguang Program by Shanghai Municipal Education Commission

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Link

http://xplorestaging.ieee.org/ielx7/7333/10031624/10210587.pdf?arnumber=10210587

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4. Hand Gesture Recognition Using Compact CNN via Surface Electromyography Signals

5. Intriguing properties of neural networks;szegedy;arXiv 1312 6199,2013

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