Deep CNN-based concrete cracks identification and quantification using image processing techniques
Author:
Publisher
Springer Science and Business Media LLC
Subject
Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42107-022-00526-9.pdf
Reference28 articles.
1. Alazawi, D. A., Hammoudi, Z. S., & Mohammed, M. N. (2021). Crack detection and geometry measurements using digital image processing. Diyala Journal of Engineering Sciences, 14(1), 11–23.
2. Ali, R., Chuah, J. H., Talip, M. S. A., Mokhtar, N., & Shoaib, M. A. (2022). Structural crack detection using deep convolutional neural networks. Automation in Construction, 133, 103989.
3. Aravind, N., Nagajothi, S., & Elavenil, S. (2021). Machine learning model for predicting the crack detection and pattern recognition of geopolymer concrete beams. Construction and Building Materials, 297, 123785.
4. Arel, I., Rose, D. C., & Karnowski, T. P. (2010). Deep machine learning-a new frontier in artificial intelligence research [research frontier]. IEEE Computational Intelligence Magazine, 5(4), 13–18.
5. Avendaño, J. C. (2020). Identification and quantification of concrete cracks using image analysis and machine learning.
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