Automatic recognition system for concrete cracks with support vector machine based on crack features-Reference-Cited by-同舟云学术

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Automatic recognition system for concrete cracks with support vector machine based on crack features

Published:2024-08-29 Issue:1 Volume:14 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Wang Rui,Chen Rui-Qi,Guo Xin-Xin,Liu Jia-Xuan,Yu Hai-Ying

Funder

Natural Science Foundation of Sichuan Province of China

Sichuan Normal University Experimental Equipment Research Project

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Link

https://www.nature.com/articles/s41598-024-71075-1.pdf

Reference48 articles.

1. Liang, D., Zhou, X.-F., Wang, S. & Liu, C.-J. Research on concrete cracks recognition based on dual convolutional neural network. KSCE J. Civ. Eng. 23(7), 3066–3074 (2019).

2. Amin, M., Agwa, I. S., Mashaan, N., Mahmood, S. & Abd-Elrahman, M. H. Investigation of the physical mechanical properties and durability of sustainable ultra-high performance concrete with recycled waste glass. Sustainability 15, 4 (2023).

3. Mohtasham Moein, M., A. Saradar, K. Rahmati, S. H. Ghasemzadeh Mousavinejad, J. Bristow, V. Aramali and M. Karakouzian, "Predictive models for concrete properties using machine learning and deep learning approaches: A review," Journal of Building Engineering, vol. 63, 2023.

4. Kumar, P., Batchu, S., Swamy, N. & Kota, S. R. Real-time concrete damage detection using deep learning for high rise structures. IEEE Access 9, 112312–112331 (2021).

5. Gupta, P. & Dixit, M. Image-based crack detection approaches: A comprehensive survey. Multimed. Tools Appl. 81(28), 40181–40229 (2022).

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