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DeepHyd : a deep learning-based artificial intelligence approach for the automated classification of hydraulic structures from LiDAR and Sonar data Cover Image E-book

DeepHyd : a deep learning-based artificial intelligence approach for the automated classification of hydraulic structures from LiDAR and Sonar data / Wenwu Tang, Shen-En Chen, John Diemer, Craig Allan, Tianyang Chen, Zachery Slocum, Tarini Shukla, Vidya Shubhash Chavan, Navanit Sri Shanmugam, Center for Applied Geographic Information Science, Department of Geography and Earth Sciences, Department of Civil and Environmental Engineering, School of Data Science, University of North Carolina at Charlotte.

Deep learning-based artificial intelligence approach for the automated classification of hydraulic structures from LiDAR and Sonar data (portion title)
Tang, Wenwu, (author.). Chen, Shen-En, (author.). Diemer, John, (author.). Allan, Craig J., 1957- (author.). Chen, Tianyang, (author.). Slocum, Zachery, (author.). Shukla, Tarini, (author.). Chavan, Vidya Shubhash, (author.). Shanmugam, Navanit Sri, (author.). North Carolina. Department of Transportation. Research and Analysis Group, (report recipient.). University of North Carolina at Charlotte. Department of Geography and Earth Sciences, (issuing body.). University of North Carolina at Charlotte. School of Data Science, (contributing body.). University of North Carolina at Charlotte. Department of Civil and Environmental Engineering, (contributing body.). University of North Carolina at Charlotte. Center for Applied Geographic Information Science, (contributing body.).

Electronic resources

https://digital.ncdcr.gov/documents/detail/563476

Record details

  • Physical Description: 1 online resource (71 pages) : illustrations, maps
  • Publisher: [Raleigh, N.C.] : [Research and Development Unit, North Carolina Department of Transportation], January 2022.

Content descriptions

General Note:
Cover title.
"January 2022."
"Report date: January 30, 2022"--Technical report documentation page.
Title from PDF cover page (viewed on July 1, 2022).
Bibliography, etc. Note:
Includes bibliographical references (pages 54-55).
Type of Report and Period Covered Note:
Final report; 07/01/2018 - 12/31/2021.
Funding Information Note:
Performed by Center for Applied Geographic Information Science, Department of Geography and Earth Sciences, University of North Carolina at Charlotte, sponsored by North Carolina Department of Transportation, Research and Development Unit PR 2019-03

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Subject:
Hydraulic structures > North Carolina > Design and construction.
Transportation engineering > North Carolina.

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MARC Record

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24510. ‡aDeepHyd : ‡ba deep learning-based artificial intelligence approach for the automated classification of hydraulic structures from LiDAR and Sonar data / ‡cWenwu Tang, Shen-En Chen, John Diemer, Craig Allan, Tianyang Chen, Zachery Slocum, Tarini Shukla, Vidya Shubhash Chavan, Navanit Sri Shanmugam, Center for Applied Geographic Information Science, Department of Geography and Earth Sciences, Department of Civil and Environmental Engineering, School of Data Science, University of North Carolina at Charlotte.
24630. ‡aDeep learning-based artificial intelligence approach for the automated classification of hydraulic structures from LiDAR and Sonar data
264 1. ‡a[Raleigh, N.C.] : ‡b[Research and Development Unit, North Carolina Department of Transportation], ‡cJanuary 2022.
300 . ‡a1 online resource (71 pages) : ‡billustrations, maps
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500 . ‡a"January 2022."
500 . ‡a"Report date: January 30, 2022"--Technical report documentation page.
504 . ‡aIncludes bibliographical references (pages 54-55).
513 . ‡aFinal report; ‡b07/01/2018 - 12/31/2021.
536 . ‡aPerformed by Center for Applied Geographic Information Science, Department of Geography and Earth Sciences, University of North Carolina at Charlotte, sponsored by North Carolina Department of Transportation, Research and Development Unit ‡fPR 2019-03
500 . ‡aTitle from PDF cover page (viewed on July 1, 2022).
650 0. ‡aHydraulic structures ‡zNorth Carolina ‡xDesign and construction.
650 0. ‡aTransportation engineering ‡zNorth Carolina.
7001 . ‡aChen, Shen-En, ‡eauthor. ‡0(CARDINAL)498601
7001 . ‡aDiemer, John, ‡eauthor. ‡0(CARDINAL)210465
7001 . ‡aAllan, Craig J., ‡d1957- ‡eauthor. ‡0(CARDINAL)316778
7001 . ‡aChen, Tianyang, ‡eauthor.
7001 . ‡aSlocum, Zachery, ‡eauthor.
7001 . ‡aShukla, Tarini, ‡eauthor.
7001 . ‡aChavan, Vidya Shubhash, ‡eauthor.
7001 . ‡aShanmugam, Navanit Sri, ‡eauthor.
7101 . ‡aNorth Carolina. ‡bDepartment of Transportation. ‡bResearch and Analysis Group, ‡ereport recipient. ‡0(CARDINAL)272064
7102 . ‡aUniversity of North Carolina at Charlotte. ‡bDepartment of Geography and Earth Sciences, ‡eissuing body. ‡0(CARDINAL)170660
7102 . ‡aUniversity of North Carolina at Charlotte. ‡bSchool of Data Science, ‡econtributing body. ‡0(CARDINAL)856082
7102 . ‡aUniversity of North Carolina at Charlotte. ‡bDepartment of Civil and Environmental Engineering, ‡econtributing body. ‡0(CARDINAL)290432
7102 . ‡aUniversity of North Carolina at Charlotte. ‡bCenter for Applied Geographic Information Science, ‡econtributing body.
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