One stage detector (RetinaNet)-based crack detection for asphalt pavements considering pavement distresses and surface objects

Author:

Tran Van PhucORCID,Tran Thai Son,Lee Hyun Jong,Kim Ki Deok,Baek Jongeun,Nguyen Thanh Tu

Funder

Sejong University

Korea Agency for Infrastructure Technology Advancement

Korea Institute of Construction Technology

Publisher

Springer Science and Business Media LLC

Subject

Safety, Risk, Reliability and Quality,Civil and Structural Engineering

Reference27 articles.

1. Oliveira H, Correia PL (2009) Automatic road crack segmentation using entropy and image dynamic thresholding. In: 2009 17th European signal processing conference. IEEE, Glasgow, Scotland, pp 622-626. ISBN:978-161-7388-76-7

2. Zhao H, Qin G, Wang X (2010) Improvement of canny algorithm based on pavement edge detection. In: 2010 3rd International congress on image and signal processing. IEEE, Yantai, China 2:964–967. https://doi.org/10.1109/CISP.2010.5646923

3. Tanaka N, Uematsu K (1998) A crack detection method in road surface images using morphology. In: Proceedings of International association for pattern recognition workshop on machine vision applications, MVA 1998. Chiba, Japan 98:154-157. ISBN: 4901122983

4. Koch C, Brilakis I (2011) Pothole detection in asphalt pavement images. Adv Eng Inform 25(3):507–515. https://doi.org/10.1016/j.aei.2011.01.002

5. Ying L, Salari E (2010) Beamlet transform-based technique for pavement crack detection and classification. Computer Aided Civil Infrastruct Eng 25(8):572–580. https://doi.org/10.1111/j.1467-8667.2010.00674.x

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