Deep Learning–Based Autonomous Road Condition Assessment Leveraging Inexpensive RGB and Depth Sensors and Heterogeneous Data Fusion: Pothole Detection and Quantification-Reference-Cited by-同舟云学术

Deep Learning–Based Autonomous Road Condition Assessment Leveraging Inexpensive RGB and Depth Sensors and Heterogeneous Data Fusion: Pothole Detection and Quantification

Published:2023-06 Issue:2 Volume:149 Page:
ISSN:2573-5438
Container-title:Journal of Transportation Engineering, Part B: Pavements
language:en
Short-container-title:J. Transp. Eng., Part B: Pavements

Author:

Huang Yu-Ting¹^ORCID,Jahanshahi Mohammad R.²,Shen Fangjia³^ORCID,Mondal Tarutal Ghosh⁴

Affiliation:

1. Ph.D. Candidate, Lyles School of Civil Engineering, Purdue Univ., 610 Purdue Mall, West Lafayette, IN 47907 (corresponding author). ORCID: .

2. Associate Professor, Lyles School of Civil Engineering and Elmore Family School of Electrical and Computer Engineering, Purdue Univ., 610 Purdue Mall, West Lafayette, IN 47907.

3. Ph.D. Student, Elmore Family School of Electrical and Computer Engineering, Purdue Univ., 610 Purdue Mall, West Lafayette, IN 47907. ORCID: .

4. Postdoctoral Fellow, Dept. of Civil, Architectural and Environmental Engineering, Missouri Univ. of Science and Technology, Rolla, MO 65401.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JPEODX.PVENG-1194

Reference51 articles.

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2. Alhashim I. and P. Wonka. 2018. “High quality monocular depth estimation via transfer learning.” Preprint submitted December 31 2018. http://arxiv.org/abs/1812.11941.

3. ASCE. 2021. “2021 report card for America’s infrastructure.” Accessed March 1 2022. https://infrastructurereportcard.org/.

4. Terrestrial laser scanner for the analysis of airport pavement geometry

5. Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory;Botshekan M.;Data-Centric Eng.,2020

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