Vision-Based Detection Method for Construction Site Monitoring by Integrating Data Augmentation and Semisupervised Learning-Reference-Cited by-同舟云学术

Vision-Based Detection Method for Construction Site Monitoring by Integrating Data Augmentation and Semisupervised Learning

Published:2024-05 Issue:5 Volume:150 Page:
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Shi Mengnan¹,Chen Chen²,Xiao Bo³^ORCID,Seo JoonOh⁴

Affiliation:

1. Postdoctoral Fellow, Dept. of Building and Real Estate, Hong Kong Polytechnic Univ., Hung Hom, Kowloon, Hong Kong.

2. Lecturer, School of Civil Engineering and Architecture, Zhejiang Univ. of Science and Technology, Hangzhou 310023, China.

3. Assistant Professor, Dept. of Civil, Environmental, and Geospatial Engineering, Michigan Technological Univ., Houghton, MI 49931 (corresponding author). ORCID: .

4. Associate Professor, Dept. of Building and Real Estate, Hong Kong Polytechnic Univ., Hung Hom, Kowloon, Hong Kong.

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JCEMD4.COENG-14388

Reference55 articles.

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3. Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types

4. SODA: A large-scale open site object detection dataset for deep learning in construction

5. Computer vision technologies for safety science and management in construction: A critical review and future research directions

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