Automated Assessment of Public Transit Bus Stops Using Computer Vision Methods-Reference-Cited by-同舟云学术

Automated Assessment of Public Transit Bus Stops Using Computer Vision Methods

Published:2023-09 Issue:5 Volume:37 Page:
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Shameli Seyed Masoud¹,Loroff Brad²,Jancev Robert³^ORCID,Borjian Shahrzad⁴,Rezazadeh Azar Ehsan⁵^ORCID

Affiliation:

1. Graduate Research Assistant, Dept. of Civil Engineering, Lakehead Univ., Thunder Bay, ON, Canada P7B 5E1.

2. Manager, Transit Services Division, City of Thunder Bay, Thunder Bay, ON, Canada P78 2ZB.

3. Product Manager, Consat Canada Inc., 1414 Lasalle Blvd., Suite 203, Sudbury, ON, Canada P3A 1Z6. ORCID: .

4. Transportation Data Specialist, City of Toronto, 100 Queen St. W., Toronto, ON, Canada M5H 2N2.

5. Assistance Professor, Dept. of Architectural Science, Toronto Metropolitan Univ., Toronto, ON, Canada M5B 2K3 (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JCCEE5.CPENG-5300

Reference28 articles.

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2. AODA (Accessibility for Ontarians with Disabilities Act). 2018. “Ontario public transit: Accessible for everyone.” Accessed February 7 2023. https://aoda.ca/ontario-public-transit/.

3. Segmentation and recognition of roadway assets from car-mounted camera video streams using a scalable non-parametric image parsing method

4. The benefits of a high-resolution analysis of transit accessibility

5. Bochkovskiy A. C. Y. Wang and H. Y. M. Liao. 2020. “YOLOv4: Optimal speed and accuracy of object detection.” Preprint submitted April 23 2020. http://arxiv.org/abs/2004.10934.