Concrete deterioration detection in sewers using machine learning algorithms: an experiment-based study-Reference-Cited by-同舟云学术

Concrete deterioration detection in sewers using machine learning algorithms: an experiment-based study

Published:2023-03-28 Issue:4 Volume:15 Page:1949-1959
ISSN:2511-2104
Container-title:International Journal of Information Technology
language:en
Short-container-title:Int. j. inf. tecnol.

Author:

Gueye Thierno,Wang Yanen^ORCID,Mushtaq Ray Tahir

Funder

Key Technologies Research and Development Program

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s41870-023-01231-9.pdf

Reference38 articles.

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3. Yang M-D, Su T-C, Pan N-F, Yang Y-F (2011) Systematic image quality assessment for sewer inspection. Expert Syst Appl 38:1766–1776. https://doi.org/10.1016/j.eswa.2010.07.103

4. Kuliczkowska E, Parka A (2017) Management of risk of tree and shrub root intrusion into sewers. Urban For urban Green 21:1–10

5. Shaikh A, Sharan P, Srikanth PC, Devi M (2021) A novel automated framework for water impurity detection. Int J Inf Technol 13:785–792. https://doi.org/10.1007/s41870-020-00601-x

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