A two-step sequential automated crack detection and severity classification process for asphalt pavements-Reference-Cited by-同舟云学术

A two-step sequential automated crack detection and severity classification process for asphalt pavements

Published:2020-10-27 Issue: Volume: Page:1-15
ISSN:1029-8436
Container-title:International Journal of Pavement Engineering
language:en
Short-container-title:International Journal of Pavement Engineering

Author:

Tran Thai Son¹^ORCID,Tran Van Phuc¹,Lee Hyun Jong¹,Flores Julius Marvin¹,Le Van Phuc²

Affiliation:

1. Civil and Environmental Engineering Department, Sejong University, Seoul, Republic of Korea

2. Campus in Ho Chi Minh City, University of Transport and Communications, Ha Noi, Vietnam

Funder

Korea Agency for Infrastructure Technology Advancement

Brain Korea 21

Sejong University

Publisher

Informa UK Limited

Subject

Mechanics of Materials,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10298436.2020.1836561

Reference35 articles.

1. Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks

2. Fan, Z. et al., 2018. Automatic pavement crack detection based on structured prediction with the convolutional neural network. arXiv preprint arXiv:1802.02208.

3. Girshick, R. et al. 2014. Rich feature hierarchies for accurate object detection and semantic segmentation. arXiv:1311.2524.

4. Girshick, R. 2015. Fast r-cnn. arXiv:1504.08083.

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