Lightweight Midrange Arm-Gesture Recognition System From mmWave Radar Point Clouds-Reference-Cited by-同舟云学术

Lightweight Midrange Arm-Gesture Recognition System From mmWave Radar Point Clouds

Published:2023-01-15 Issue:2 Volume:23 Page:1261-1270
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Xie Haihua¹^ORCID,Han Peidong²,Li Changhe³^ORCID,Chen Yiqin⁴,Zeng Sanyou¹^ORCID

Affiliation:

1. School of Mechanical Engineering and Electronic Information and the Key Laboratory of Geological Survey and Evaluation of Ministry of Education, China University of Geosciences, Wuhan, China

2. Southwest Electronics and Telecommunication Technology Research Institute, Chengdu, China

3. School of Automation, China University of Geosciences, Wuhan, China

4. Shenzhen TianDing Microwave Technology Company Ltd, Shenzhen, China

Funder

Opening Fund of the Key Laboratory of GeologicalSurvey and Evaluation of Ministry of Education

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities, China University of Geosciences, Wuhan

Hubei Provincial Natural Science Foundation of China

Higher Education Discipline Innovation Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10017147/09979773.pdf?arnumber=9979773

Reference33 articles.

1. Convolutional LSTM network: A machine learning approach for precipitation nowcasting;shi;Proc Adv Neural Inf Process Syst,2016

2. Real-Time Macro Gesture Recognition Using Efficient Empirical Feature Extraction With Millimeter-Wave Technology

3. PointNet++: Deep hierarchical feature learning on point Sets in a metric space;qi;Proc Adv Neural Inf Process Syst,2017

4. Optimization of Diode Structures for Monolithic Integrated Microwave Circuits

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