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Parallel convolutional neural network toward high efficiency and robust structural damage identification

Author(s): (School of Civil Engineering, Guangzhou University, Guangzhou, China)
(Dongguan Rail Transit Co., Ltd., Dongguan, China)
(Research Center of Wind Engineering and Engineering Vibration, Guangzhou University, Guangzhou, China)
(School of Mechanics, Civil Engineering and Architecture, Northwestern Polytechnical University, Xi’an, China)
ORCID (Guangzhou Institute of Building Science Group Co., Ltd., Guangzhou, China)
ORCID (School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China)
Medium: journal article
Language(s): English
Published in: Structural Health Monitoring, , n. 6, v. 22
Page(s): 147592172311587
DOI: 10.1177/14759217231158786
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: 10.1177/14759217231158786.
  • About this
    data sheet
  • Reference-ID
    10730057
  • Published on:
    30/05/2023
  • Last updated on:
    14/01/2024
 
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