Advanced machine learning methods for autonomous classification of ground vehicles with acoustic data

Liu, X., Li, Q., Liang, J. et al. (9 more authors) (2022) Advanced machine learning methods for autonomous classification of ground vehicles with acoustic data. In: Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV. SPIE.Defense + Commercial Sensing, 04-07 Apr 2022, Tallahassee, FL, USA. Proceedings of SPIE, 12113 . SPIE - Society of Photo-optical Instrumentation Engineers , 121131P.

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2022 Society of Photo Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, or modification of the contents of the publication are prohibited.
Keywords: Machine learning; Gaussian process; acoustic data; classification; surveillance
Dates:
  • Accepted: 15 November 2021
  • Published (online): 6 June 2022
  • Published: 6 June 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Funding Information:
FunderGrant number
United States Department of Defensen/a
UK MOD University Defence Research Collaboration (UDRC)W911NF-20-2-0225
Depositing User: Symplectic Sheffield
Date Deposited: 24 Mar 2022 08:21
Last Modified: 21 Jun 2023 10:05
Published Version: http://www.spie.org/SI210call
Status: Published
Publisher: SPIE - Society of Photo-optical Instrumentation Engineers
Series Name: Proceedings of SPIE
Refereed: Yes
Identification Number: https://doi.org/10.1117/12.2618105
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