Discussion of “Image Processing–Based Framework for Determining Deterioration in Sewer Pipe Defects”-Reference-Cited by-同舟云学术

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Discussion of “Image Processing–Based Framework for Determining Deterioration in Sewer Pipe Defects”

Published:2024-03 Issue:1 Volume:30 Page:
ISSN:1076-0342
Container-title:Journal of Infrastructure Systems
language:en
Short-container-title:J. Infrastruct. Syst.

Author:

Patil Rushabh Nitin¹^ORCID,Gavande Abhishek Sanjeev²^ORCID

Affiliation:

1. Independent Researcher, Dept. of Civil Engineering, Purdue Univ., West Lafayette, IN 47906 (corresponding author). ORCID: .

2. Independent Researcher, Dept. of Civil and Environmental Engineering, Univ. of New South Wales (UNSW), Sydney, NSW, Australia. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JITSE4.ISENG-2297

Reference8 articles.

1. Avendano C. 2020. “Identification and quantification of concrete cracks using image analysis and machine learning.” Doctoral dissertation School of Architecture and the Built Environment KTH Royal Institute of Technology.

2. Impact of Packet Loss Rate on Quality of Compressed High Resolution Videos

3. Cleys T. D. Buonadonna S. Cancilla and J. Starr. 2017. “Next generation laser profiling.” In Proc. Pipelines 226–233. Reston VA: ASCE. https://doi.org/10.1061/9780784480885.022.

4. Vision-Based Defect Inspection and Condition Assessment for Sewer Pipes: A Comprehensive Survey

5. Investigations of Fatigue Crack Detection Using Local Vibration Techniques: Numerical and Experimental Studies

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