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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

Search for related items by subject

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