Hierarchical Radar Data Analysis for Activity and Personnel Recognition

Li, X., Li, Z., Fioranelli, F. et al. (3 more authors) (2020) Hierarchical Radar Data Analysis for Activity and Personnel Recognition. Remote Sensing, 12 (14). 2237. ISSN 2072-4292

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Item Type: Article
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© 2019 by the authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.

Keywords: radar sensors; activity classification; gait analysis; personnel recognition; mircro-doppler; machine learning
Dates:
  • Published: 12 July 2020
  • Accepted: 9 July 2020
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Medical and Biological Engineering (iMBE) (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 03 Oct 2024 14:54
Last Modified: 03 Oct 2024 14:54
Status: Published
Publisher: MDPI
Identification Number: 10.3390/rs12142237
Sustainable Development Goals:
  • Sustainable Development Goals: Goal 7: Affordable and Clean Energy
Open Archives Initiative ID (OAI ID):

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