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Geoacoustic and geophysical data‐driven seafloor sediment classification through machine learning algorithms with property‐centered oversampling techniques

Author(s): (Department of Civil and Environmental Engineering Incheon National University Incheon Republic of Korea)
(School of Civil Environmental and Architectural Engineering Korea University Seoul Republic of Korea)
(Department of Construction and Disaster Prevention Engineering Daejeon University Daejeon Republic of Korea)
Medium: journal article
Language(s): English
Published in: Computer-Aided Civil and Infrastructure Engineering, , n. 14, v. 39
Page(s): 2105-2121
DOI: 10.1111/mice.13126
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.13126.
  • About this
    data sheet
  • Reference-ID
    10749649
  • Published on:
    14/01/2024
  • Last updated on:
    20/09/2024
 
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