Automatic recognition and analysis system of asphalt pavement cracks using interleaved low-rank group convolution hybrid deep network and SegNet fusing dense condition random field

Author:

Li Gang,Liu Qiangwei,Ren Wei,Qiao Wenting,Ma Biao,Wan Jian

Funder

Key Research and Development Program of Guangxi

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference52 articles.

1. Pixel-level cracking detection on 3D asphalt pavement images through deep-learning- based CrackNet-V;Fei;IEEE Trans. Intell. Transp. Syst.,2020

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3. Analysis of edge-detection techniques for crack identification in bridges;Abdel-Qader;J. Comput. Civil Eng.,2003

4. The design of glass crack detection system based on image preprocessing technology;Yiyang,2014

5. Image processing algorithm for real-time crack inspection in hole expansion test;Choi;Int. J. Precis. Eng. Manuf.,2019

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