Feature detection and classification in buried pipes using LiDAR technology

Karnezis, A., Worley, R., Blight, A. et al. (3 more authors) (2025) Feature detection and classification in buried pipes using LiDAR technology. In: Proceedings of the The 21st International Computing & Control in the Water Industry Conference,, CCWI 2025. The 21st International Computing & Control in the Water Industry Conference,, CCWI 2025, 01-03 Sep 2025, Sheffield, UK. University of Sheffield.

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Item Type: Proceedings Paper
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© 2025 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Keywords: LiDAR; Feature detection; Decision making
Dates:
  • Accepted: 21 May 2025
  • Published (online): 26 August 2025
  • Published: 26 August 2025
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering
Funding Information:
Funder
Grant number
EUROPEAN COMMISSION - HORIZON EUROPE
101189847
Depositing User: Symplectic Sheffield
Date Deposited: 14 Jul 2025 14:45
Last Modified: 09 Sep 2025 11:21
Status: Published
Publisher: University of Sheffield
Refereed: Yes
Identification Number: 10.15131/shef.data.29920931.v1
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