Analyzing Safety Risk Imposed by Jobsite Debris to Nearby Built Environments Using Geometric Digital Twins and Vision-Based Deep Learning-Reference-Cited by-同舟云学术

Analyzing Safety Risk Imposed by Jobsite Debris to Nearby Built Environments Using Geometric Digital Twins and Vision-Based Deep Learning

Published:2022-11 Issue:6 Volume:36 Page:
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Kamari Mirsalar¹,Kim Jaeyoon²,Ham Youngjib³

Affiliation:

1. Ph.D. Candidate, Dept. of Construction Science, Texas A&M Univ., 3137 TAMU, College Station, TX 77843.

2. Ph.D. Student, Dept. of Construction Science, Texas A&M Univ., 3137 TAMU, College Station, TX 77843.

3. Associate Professor, Dept. of Construction Science, Texas A&M Univ., Francis Hall 329B, 3137 TAMU, College Station, TX 77843 (corresponding author).

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.1943-5487.0001044

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3. Advancing Safety by In-Depth Assessment of Workers Attention and Perception

4. Detection, classification, and mapping of U.S. traffic signs using google street view images for roadway inventory management

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