Toward High-Precision Crack Detection in Concrete Bridges Using Deep Learning-Reference-Cited by-同舟云学术

Toward High-Precision Crack Detection in Concrete Bridges Using Deep Learning

Published:2023-06 Issue:3 Volume:37 Page:
ISSN:0887-3828
Container-title:Journal of Performance of Constructed Facilities
language:en
Short-container-title:J. Perform. Constr. Facil.

Author:

Ni Youhao¹,Mao Jianxiao²,Wang Hao³^ORCID,Xi Zhuo⁴,Xu Yinfei⁵

Affiliation:

1. Ph.D. Candidate, Key Laboratory of C&PC Structures of Ministry of Education, Southeast Univ., Nanjing 211189, China.

2. Associate Professor, Key Laboratory of C&PC Structures of Ministry of Education, Southeast Univ., Nanjing 211189, China.

3. Professor, Key Laboratory of C&PC Structures of Ministry of Education, Southeast Univ., Nanjing 211189, China (corresponding author). ORCID: .

4. Professor, Key Laboratory of C&PC Structures of Ministry of Education, Southeast Univ., Nanjing 211189, China.

5. Master’s Student, Key Laboratory of C&PC Structures of Ministry of Education, Southeast Univ., Nanjing 211189, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

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

Link

https://ascelibrary.org/doi/pdf/10.1061/JPCFEV.CFENG-4275

Reference52 articles.

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2. A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications

3. Bochkovskiy A. C. Y. Wang and H. M. Liao. 2020. “Yolov4: Optimal speed and accuracy of object detection.” Preprint submitted April 23 2020. https://arxiv.org/abs/2004.10934.

4. Cao G. Y. Zhao R. Ni L. Yu and H. Tian. 2010. “Forensic detection of median filtering in digital images.” In Proc. IEEE Int. Conf. on Multimedia and Expo 89–94. New York: IEEE. https://doi.org/10.1109/ICME.2010.5583869.

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

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