Automated Identification of Pavement Structural Distress Using State-of-the-Art Object Detection Models and Nondestructive Testing-Reference-Cited by-同舟云学术

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Automated Identification of Pavement Structural Distress Using State-of-the-Art Object Detection Models and Nondestructive Testing

Published:2024-07 Issue:4 Volume:38 Page:
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Guo Xiaogang¹^ORCID,Wang Ning²^ORCID

Affiliation:

1. Postdoctoral Research Associate, School of Concrete and Construction Management, Middle Tennessee State Univ., Murfreesboro, TN 37132 (corresponding author). ORCID: .

2. Assistant Professor, School of Concrete and Construction Management, Middle Tennessee State Univ., Murfreesboro, TN 37132. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JCCEE5.CPENG-5864

Reference64 articles.

1. Condition assessment of concrete-made structures using ground penetrating radar

2. Indirect diagnosis of pavement structural damages using surface GPR reflection techniques

3. Machine learning algorithms for monitoring pavement performance

4. A BIM-based construction quality management model and its applications

5. Data Mining. 2011. Data mining: Practical machine learning tools and techniques. Amsterdam, Netherlands: Elsevier.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Identification of internal voids in pavement based on improved knowledge distillation technology;Case Studies in Construction Materials;2024-12

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