Learning methods for dynamic topic modeling in automated behaviour analysis

Isupova, O., Kuzin, D. and Mihaylova, L. (2018) Learning methods for dynamic topic modeling in automated behaviour analysis. IEEE Transactions on Neural Networks and Learning Systems, 29 (9). pp. 3980-3993. ISSN 2162-237X

Abstract

Metadata

Authors/Creators:
  • Isupova, O.
  • Kuzin, D.
  • Mihaylova, L.
Copyright, Publisher and Additional Information: © 2017 IEEE. This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/
Keywords: Behavior analysis; expectation maximization; learning dynamic topic models; unsupervised learning; variational Bayesian approach; video analytics
Dates:
  • Accepted: 25 July 2017
  • Published (online): 27 September 2017
  • Published: September 2018
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
EUROPEAN COMMISSION - FP6/FP7TRAX - 607400
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/K021516/1
Depositing User: Symplectic Sheffield
Date Deposited: 20 Apr 2017 13:52
Last Modified: 22 Jul 2020 10:54
Published Version: https://doi.org/10.1109/TNNLS.2017.2735364
Status: Published
Publisher: IEEE
Refereed: Yes
Identification Number: https://doi.org/10.1109/TNNLS.2017.2735364
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