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Numerical Modeling of GPR for Underground Multi-Pipes Detection by Combining GprMax and Deep Learning Model.

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Title: Numerical Modeling of GPR for Underground Multi-Pipes Detection by Combining GprMax and Deep Learning Model.
Authors: Qiang Guo1, Pengju Yang1,2, pjyang@fudan.edu.cn, Rui Wu1,3, Yuqiang Zhang1
Source: Progress in Electromagnetics Research M; 2024, Vol. 128, p99-113, 15p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 179442091
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Numerical Modeling of GPR for Underground Multi-Pipes Detection by Combining GprMax and Deep Learning Model.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=179442091
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.2528/PIERM24062603
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 15
        StartPage: 99
    Titles:
      – TitleFull: Numerical Modeling of GPR for Underground Multi-Pipes Detection by Combining GprMax and Deep Learning Model.
        Type: main
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            NameFull: Qiang Guo
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            NameFull: Pengju Yang
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            NameFull: Rui Wu
      – PersonEntity:
          Name:
            NameFull: Yuqiang Zhang
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            – D: 01
              M: 06
              Text: 2024
              Type: published
              Y: 2024
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              Value: 19378726
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              Value: 128
          Titles:
            – TitleFull: Progress in Electromagnetics Research M
              Type: main
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