Tunnel Crack Direction Classification Based on BP Neural Network-Reference-Cited by-同舟云学术

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Tunnel Crack Direction Classification Based on BP Neural Network

Published:2023-09-22 Issue: Volume:38 Page:327-336
ISSN:
Container-title:Proceedings of the 2023 3rd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum
language:
Short-container-title:

Author:

Dai Chunquan¹^ORCID,Zhang Huidi²^ORCID,Zhou Zhaochen²^ORCID,Jiang Kun²^ORCID

Affiliation:

1. Shandong Civil Engineering Disaster Prevention and Mitigation Laboratory, Shandong University of Science and Technology, China

2. School of Civil Engineering and Architecture, Shandong University of Science and Technology, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3660395.3660451

Reference27 articles.

1. A review of tunnel lining crack detection algorithm based on machine vision [J];Yuan Weiqi;Journal of Instrumentation,2017

2. Diagnosis of cracks in shield tunnel lining based on digital images [J];Li Qingtong;Chinese Journal of Rock Mechanics and Engineering,2020

3. Research on image processing for crack detection in tunnels [J];Wang Rui;Railway Standard Design,2014

4. Jianghai Liao. Research on rapid detection method of tunnel surface diseases [D]. Shenzhen University, 2020.

5. Dissecting self-supervised learning methods for surgical computer vision

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