Application of signal processing and support vector machine to transverse cracking detection in asphalt pavement
Author:
Publisher
Springer Science and Business Media LLC
Subject
Metals and Alloys,General Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11771-021-4779-6.pdf
Reference24 articles.
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3. MEI Qi-pei, GÜL M. A cost effective solution for pavement crack inspection using cameras and deep neural networks [J]. Construction and Building Materials, 2020, 256: 119397. DOI: https://doi.org/10.1016/j.conbuildmat.2020.119397.
4. INKOOM S, SOBANJO J, BARBU A, NIU Xu-feng. Pavement crack rating using machine learning frameworks: Partitioning, bootstrap forest, boosted trees, naïve Bayes, and K-nearest neighbors [J]. Journal of Transportation Engineering, Part B: Pavements, 2019, 145(3): 04019031. DOI: https://doi.org/10.1061/jpeodx.0000126.
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