A Case Study on Multilane Roundabout Capacity Evaluation Using Computer Vision and Deep Learning-Reference-Cited by-同舟云学术

A Case Study on Multilane Roundabout Capacity Evaluation Using Computer Vision and Deep Learning

Published:2022-05 Issue:3 Volume:36 Page:
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Khekare Pranav¹^ORCID,Bonthu Sai¹^ORCID,Hunt Victor²,Helmicki Arthur³,Lee Kevin⁴

Affiliation:

1. Research Assistant, Dept. of Electrical Engineering and Computer Science, Univ. of Cincinnati, Cincinnati, OH 45221. ORCID: .

2. Professor, Dept. of Electrical Engineering and Computer Science, Univ. of Cincinnati, Cincinnati, OH 45221.

3. Professor, Dept. of Electrical Engineering and Computer Science, Univ. of Cincinnati, Cincinnati, OH 45221 (corresponding author).

4. Principal Engineer, Kittelson & Associates, Inc., 11 Garfield Place, Cincinnati, OH 45202.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0001007

Reference22 articles.

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3. Modeling Origin-Destination Effects on Roundabout Operations and Inflow Control

4. Dutta A. A. Gupta and A. Zissermann. 2016. “VGG image annotator (VIA).” Accessed October 21 2019. https://www.robots.ox.ac.uk/∼vgg/software/via/.

5. Dutta A. and A. Zisserman. 2019. “The VIA annotation software for images audio and video.” In Proc. 27th ACM Int. Conf. on Multimedia MM ’19. New York: Association of Computer Machinery.

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