Benefits of ensemble models in road pavement cracking classification
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2020/02/24
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Indian UGC (journal)
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Refrences66
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Citations16
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Francisco J. Rodriguez‐Lozano Department of Electronic and Computer Engineering Universidad de Córdoba Córdoba Spain
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Fernando León‐García Department of Electronic and Computer Engineering Universidad de Córdoba Córdoba Spain
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Juan C. Gámez‐Granados Department of Electronic and Computer Engineering Universidad de Córdoba Córdoba Spain
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Jose M. Palomares Department of Electronic and Computer Engineering Universidad de Córdoba Córdoba Spain
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J. Olivares Department of Electronic and Computer Engineering Universidad de Córdoba Córdoba Spain
Abstract
Cite
Rodriguez‐Lozano, Francisco J., et al. “Benefits of Ensemble Models in Road Pavement Cracking Classification”. Computer-Aided Civil and Infrastructure Engineering, vol. 35, no. 11, 2020, pp. 1194-08, https://doi.org/10.1111/mice.12543.
Rodriguez‐Lozano, F. J., León‐García, F., Gámez‐Granados, J. C., Palomares, J. M., & Olivares, J. (2020). Benefits of ensemble models in road pavement cracking classification. Computer-Aided Civil and Infrastructure Engineering, 35(11), 1194-1208. https://doi.org/10.1111/mice.12543
Rodriguez‐Lozano, Francisco J., Fernando León‐García, Juan C. Gámez‐Granados, Jose M. Palomares, and J. Olivares. “Benefits of Ensemble Models in Road Pavement Cracking Classification”. Computer-Aided Civil and Infrastructure Engineering 35, no. 11 (2020): 1194-1208. https://doi.org/10.1111/mice.12543.
Rodriguez‐Lozano FJ, León‐García F, Gámez‐Granados JC, Palomares JM, Olivares J. Benefits of ensemble models in road pavement cracking classification. Computer-Aided Civil and Infrastructure Engineering. 2020;35(11):1194-208.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Technology
Building construction
Architectural engineering
Structural engineering of buildings
Technology
Engineering (General)
Civil engineering (General)
Technology
Engineering (General)
Civil engineering (General)
Transportation engineering
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Recent advances in control algorithms for smart structures and machines | Expert Systems |
| 2017 | |
| Automatic classification of pavement crack using deep convolutional neural network | International Journal of Pavement Engineering |
| 2018 | |
| Proceedings of the 2nd International Asia Conference on Informatics in Control, Automation and Robotics ‐ Volume 3 | 2010 | |||
| Classification and regression trees | 1984 | |||
| A talk at the Stanford artificial project | 1968 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| An average pooling designed Transformer for robust crack segmentation | Automation in Construction |
| 2024 | |
| On Enhancing Crack Semantic Segmentation Using StyleGAN and Brownian Bridge Diffusion | IEEE Access |
| 2024 | |
Automatic Classification of Pavement Type and Service Age Benchmarked with Standard Texture Databases Using the Machine Learning Method: A Pilot Study | Transportation Research Record: Journal of the Transportation Research Board |
| 2024 | |
Approximation in scour depth around spur dikes using novel hybrid ensemble data-driven model | Water Science & Technology |
| 2024 | |
| Recent computer vision applications for pavement distress and condition assessment | Automation in Construction |
| 8 | 2023 |
Citations Analysis
The category
Technology: Engineering (General). Civil engineering (General) 14
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Measuring aggregate morphologies based on three‐dimensional curvature analysis and was published in 2021. The most recent citation comes from a 2024 study titled An average pooling designed Transformer for robust crack segmentation. This article reached its peak citation in 2024, with 4 citations. It has been cited in 10 different journals, 30% of which are open access. Among related journals, the Computer-Aided Civil and Infrastructure Engineering cited this research the most, with 5 citations. The chart below illustrates the annual citation trends for this article.