Automated Detection and Segmentation of Mechanical, Electrical, and Plumbing Components in Indoor Environments by Using the YOLACT++ Architecture-Reference-Cited by-同舟云学术

Automated Detection and Segmentation of Mechanical, Electrical, and Plumbing Components in Indoor Environments by Using the YOLACT++ Architecture

Published:2024-08 Issue:8 Volume:150 Page:
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Shamsollahi Dena¹^ORCID,Moselhi Osama²,Khorasani Khashayar³^ORCID

Affiliation:

1. Ph.D. Candidate, Dept. of Building, Civil and Environmental Engineering, Concordia Univ., Montréal, QC, Canada H3G 1M8 (corresponding author). ORCID: .

2. Professor, Dept. of Building, Civil and Environmental Engineering, Concordia Univ., Montréal, QC, Canada H3G 1M8; Director of the Centre for Innovation in Construction and Infrastructure Engineering and Management, Gina Cody School of Engineering and Computer Science, Concordia Univ., Montréal, QC, Canada H3G 1M8.

3. Professor, Dept. of Electrical and Computer Engineering, Concordia Univ., Montréal, QC, Canada H3G 1M8. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JCEMD4.COENG-15115

Reference74 articles.

1. Using digital photogrammetry for pipe-works progress tracking1This paper is one of a selection of papers in this Special Issue on Construction Engineering and Management.

2. Cost Reduction Techniques on MEP Projects

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4. Generating real-world-like labelled synthetic datasets for construction site applications

5. Bolya D. C. Zhou F. Xiao and Y. J. Lee. 2019. “YOLACT: Real-time instance segmentation.” In Proc. IEEE Int. Conf. Computer Vision (ICCV) 9156–9165. New York: IEEE.