mmCMD: Continuous Motion Detection From Visualized Radar Micro-Doppler Signatures Using Visual Object Detection Techniques-Reference-Cited by-同舟云学术

mmCMD: Continuous Motion Detection From Visualized Radar Micro-Doppler Signatures Using Visual Object Detection Techniques

Published:2024-02-01 Issue:3 Volume:24 Page:3394-3405
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Xu Zhimeng¹^ORCID,Ding Junyin¹^ORCID,Zhang Shanshan¹^ORCID,Gao Yueming¹^ORCID,Chen Liangqin¹^ORCID,Vasić Željka Lučev²^ORCID,Cifrek Mario²^ORCID,Chen Zhizhang David³^ORCID

Affiliation:

1. College of Physical and Information Engineering, Fuzhou University, Fuzhou, China

2. Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia

3. Department of Electrical and Computer Engineering, Dalhousie University, Halifax, Canada

Funder

National Key Research and Development Program of China

Natural Science Foundation of Fujian Province

National Natural Science Foundation of China

Major Program of the Department of Science and Technology of Fujian Province

Science and Technology Innovation Platform Project of Fuzhou City

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10418056/10364363.pdf?arnumber=10364363

Reference40 articles.

1. World Population Prospects 2022

2. E²(GO)MOTION: Motion Augmented Event Stream for Egocentric Action Recognition

3. Multiscale Deep Feature Learning for Human Activity Recognition Using Wearable Sensors

4. S-THAD: a framework for sensor-based temporal human activity detection from continuous data streams

5. Multitarget Physical Activities Monitoring and Classification Using a V-Band FMCW Radar

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