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Site classification using deep‐learning‐based image recognition techniques

Author(s): ORCID (College of Civil and Transportation Engineering Hohai University Nanjing China)
(Department of Civil and Natural Resources Engineering University of Canterbury Christchurch New Zealand)
ORCID (Department of Civil Engineering University of Tabriz Tabriz Iran)
(Key Laboratory of Earthquake Engineering and Engineering Vibration Institute of Engineering Mechanics China Earthquake Administration Harbin China)
(Key Laboratory of Earthquake Engineering and Engineering Vibration Institute of Engineering Mechanics China Earthquake Administration Harbin China)
(Key Laboratory of Earthquake Engineering and Engineering Vibration Institute of Engineering Mechanics China Earthquake Administration Harbin China)
Medium: journal article
Language(s): English
Published in: Earthquake Engineering and Structural Dynamics, , n. 8, v. 52
Page(s): 2323-2338
DOI: 10.1002/eqe.3801
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: 10.1002/eqe.3801.
  • About this
    data sheet
  • Reference-ID
    10708840
  • Published on:
    21/03/2023
  • Last updated on:
    02/09/2023
 
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