FFCSLT: A Deep Learning Model for Traffic Police Hand Gesture Recognition Using Surface Electromyographic Signals-Reference-Cited by-同舟云学术

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FFCSLT: A Deep Learning Model for Traffic Police Hand Gesture Recognition Using Surface Electromyographic Signals

Published:2024-04-15 Issue:8 Volume:24 Page:13640-13655
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Ma Wenxuan¹^ORCID,Song Ge²^ORCID,Zeng Qingtian³^ORCID,Zhang Hongxin¹^ORCID,Zou Minghao³^ORCID,Zhao Ziqi³^ORCID

Affiliation:

1. College of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China

2. College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, China

3. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Science and Technology Development Fund of Shandong Province of China

Taishan Scholar Program of Shandong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10500449/10462028.pdf?arnumber=10462028

Reference50 articles.

1. Human Activity Recognition Based on Motion Sensor Using U-Net

2. Intelligent Transportation Application and Analysis for Multi-Sensor Information Fusion of Internet of Things

3. Neuromorphic Edge Computing for Biomedical Applications: Gesture Classification Using EMG Signals

4. Deep learning for healthcare applications based on physiological signals: A review

5. A Comparison of EEG Preprocessing Methods using Time Delay Neural Networks

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