Automatic Recognition of Workers’ Motions in Highway Construction by Using Motion Sensors and Long Short-Term Memory Networks-Reference-Cited by-同舟云学术

Automatic Recognition of Workers’ Motions in Highway Construction by Using Motion Sensors and Long Short-Term Memory Networks

Published:2021-03 Issue:3 Volume:147 Page:04020184
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Kim Kinam¹,Cho Yong K.²^ORCID

Affiliation:

1. Graduate Student, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0355.

2. Associate Professor, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0355 (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CO.1943-7862.0002001

Reference31 articles.

1. Akhavian R. and A. H. Behzadan. 2016a. “Productivity analysis of construction worker activities using smartphone sensors.” In Proc. 16th Int. Conf. on Computing in Civil and Building Engineering 1067–1074. Tokyo: Japan Society of Civil Engineers.

2. Smartphone-based construction workers' activity recognition and classification

3. Identifying poses of safe and productive masons using machine learning

4. Automated detection and classification of construction workers' loss of balance events using wearable insole pressure sensors

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