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Enriched and discriminative convolutional neural network features for pedestrian re‐identification and trajectory modeling

Author(s): (Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology Hong Kong China)
(Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology Hong Kong China)
(School of Architecture, Building and Civil Engineering Loughborough University Loughborough UK)
(Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology Hong Kong China)
Medium: journal article
Language(s): English
Published in: Computer-Aided Civil and Infrastructure Engineering, , n. 5, v. 37
Page(s): 573-592
DOI: 10.1111/mice.12750
Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1111/mice.12750.
  • About this
    data sheet
  • Reference-ID
    10624410
  • Published on:
    26/08/2021
  • Last updated on:
    23/03/2022
 
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