Deep Learning–Based Fully Automated Pavement Crack Detection on 3D Asphalt Surfaces with an Improved CrackNet-Reference-Cited by-同舟云学术

Deep Learning–Based Fully Automated Pavement Crack Detection on 3D Asphalt Surfaces with an Improved CrackNet

Published:2018-09 Issue:5 Volume:32 Page:04018041
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Zhang Allen¹,Wang Kelvin C. P.²,Fei Yue³,Liu Yang³,Tao Siyu⁴,Chen Cheng⁵,Li Joshua Q.⁶,Li Baoxian⁷

Affiliation:

1. Assistant Professor, Dept. of Civil Engineering, Southwest Jiaotong Univ., Chengdu 610031, China; Postdoctoral Fellow, Dept. of Civil and Environmental Engineering, Oklahoma State Univ., 207 Engineering South, Stillwater, OK 74078.

2. Professor, Dept. of Civil and Environmental Engineering, Oklahoma State Univ., 207 Engineering South, Stillwater, OK 74078; Professor, Dept. of Civil Engineering, Southwest Jiaotong Univ., Chengdu 610031, China.

3. Ph.D. Student, Dept. of Civil and Environmental Engineering, Oklahoma State Univ., 207 Engineering South, Stillwater, OK 74078.

4. Assistant Professor, School of Transportation and Logistics, Southwest Jiaotong Univ., Chengdu 610031, China (corresponding author).

5. Senior Research Engineer, Dept. of Civil and Environmental Engineering, Oklahoma State Univ., 207 Engineering South, Stillwater, OK 74078.

6. Assistant Professor, Dept. of Civil and Environmental Engineering, Oklahoma State Univ., 207 Engineering South, Stillwater, OK 74078.

7. Ph.D. Student, Dept. of Civil Engineering, Southwest Jiaotong Univ., Chengdu 610031, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000775

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4. Evaluating Pavement Cracks with Bidimensional Empirical Mode Decomposition

5. Avila M. S. Begot F. Duculty and T. S. Nguyen. 2014. “2D image based road pavement crack detection by calculating minimal paths and dynamic programming.” In Proc. Int. Conf. on Image Processing 783–787. Piscataway NJ: IEEE.

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