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Predicting tree failure likelihood for utility risk mitigation via a convolutional neural network

Author(s): ORCID (Department of Civil and Environmental Engineering, University of Massachusetts Amherst, Massachusetts, USA)
ORCID (Department of Civil and Environmental Engineering, University of Massachusetts Amherst, Massachusetts, USA)
ORCID (Department of Environmental Conservation, University of Massachusetts Amherst, Massachusetts, USA)
ORCID (Department of Civil and Environmental Engineering, University of Massachusetts Amherst, Massachusetts, USA)
ORCID (Department of Environmental Conservation, University of Massachusetts Amherst, Massachusetts, USA)
Medium: journal article
Language(s): English
Published in: Sustainable and Resilient Infrastructure, , n. 6, v. 8
Page(s): 1-17
DOI: 10.1080/23789689.2023.2233759
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: 10.1080/23789689.2023.2233759.
  • About this
    data sheet
  • Reference-ID
    10738210
  • Published on:
    03/09/2023
  • Last updated on:
    14/01/2024
 
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