Author:
Rill-García Rodrigo,Dokladalova Eva,Dokládal Petr
Subject
Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications
Reference57 articles.
1. E. Coquelle, J.-L. Gautier, P. Dokládal, Automatic assessment of a road surface condition, in: 7th Symposium on Pavement Surface Characteristics, Surf, Norfolk, Virginia, 2012.
2. X. Yang, H. Li, Y. Yu, X. Luo, T. Huang, X. Yang, Automatic Pixel-Level Crack Detection and Measurement Using Fully Convolutional Network, Computer-Aided Civil and Infrastructure Engineering 33 (12) (2018) 1090–1109, _eprint: http://onlinelibrary.wiley.com/doi/abs/10.1111/mice.12412.
3. A Survey On Road Crack Detection Techniques;Bhat,2020
4. CrackTree: Automatic crack detection from pavement images;Zou;Pattern Recogn. Lett.,2012
5. U. Escalona, F. Arce, E. Zamora, J.H. Sossa Azuela, Fully Convolutional Networks for Automatic Pavement Crack Segmentation, Computación y Sistemas 23 (2) (2019) 451–460–460, number: 2. doi:10.13053/cys-23-2-3047. https://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/3047.
Cited by
14 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献