Yantao Yu 
- (2024): An unsupervised low-light image enhancement method for improving V-SLAM localization in uneven low-light construction sites. In: Automation in Construction, v. 162 (June 2024).
- (2024): Learning multi-granular worker intentions from incomplete visual observations for worker-robot collaboration in construction. In: Automation in Construction, v. 158 (February 2024).
- (2023): Identification and Classification of Physical Fatigue in Construction Workers Using Linear and Nonlinear Heart Rate Variability Measurements. In: Journal of Construction Engineering and Management, v. 149, n. 7 (July 2023).
- (2023): Recovering building information model from 2D drawings for mechanical, electrical and plumbing systems of ageing buildings. In: Automation in Construction, v. 152 (August 2023).
- (2023): Intelligent and Computer Technologies’ Application in Construction. In: Buildings, v. 13, n. 3 (26 February 2023).
- (2022): Automated Selection and Localization of Mobile Cranes in Construction Planning. In: Buildings, v. 12, n. 5 (24 April 2022).
- (2022): Quantifying the Effect of Mental Stress on Physical Stress for Construction Tasks. In: Journal of Construction Engineering and Management, v. 148, n. 3 (March 2022).
- (2021): Posture-related data collection methods for construction workers: A review. In: Automation in Construction, v. 124 (April 2021).
- (2020): Automated PPE-Tool pair check system for construction 2 safety using smart IoT. In: Journal of Building Engineering, v. 32 (November 2020).
- (2020): Construction Activity Recognition and Ergonomic Risk Assessment Using a Wearable Insole Pressure System. In: Journal of Construction Engineering and Management, v. 146, n. 7 (July 2020).
- (2019): Capturing and Understanding Workers’ Activities in Far-Field Surveillance Videos with Deep Action Recognition and Bayesian Nonparametric Learning. In: Computer-Aided Civil and Infrastructure Engineering, v. 34, n. 4 (March 2019).
- (2018): Automatic Pixel-Level Crack Detection and Measurement Using Fully Convolutional Network. In: Computer-Aided Civil and Infrastructure Engineering, v. 33, n. 12 (November 2018).
- (2020): Combining deep features and activity context to improve recognition of activities of workers in groups. In: Computer-Aided Civil and Infrastructure Engineering, v. 35, n. 9 (February 2020).
- (2019): An automatic and non-invasive physical fatigue assessment method for construction workers. In: Automation in Construction, v. 103 (July 2019).
- (2019): Joint-Level Vision-Based Ergonomic Assessment Tool for Construction Workers. In: Journal of Construction Engineering and Management, v. 145, n. 5 (May 2019).
- (2019): Automatic Biomechanical Workload Estimation for Construction Workers by Computer Vision and Smart Insoles. In: Journal of Computing in Civil Engineering, v. 33, n. 3 (May 2019).
- (2018): Image-and-Skeleton-Based Parameterized Approach to Real-Time Identification of Construction Workers' Unsafe Behaviors. In: Journal of Construction Engineering and Management, v. 144, n. 6 (June 2018).
- (2017): The availability of wearable-device-based physical data for the measurement of construction workers' psychological status on site: From the perspective of safety management. In: Automation in Construction, v. 82 (October 2017).
- (2017): An experimental study of real-time identification of construction workers' unsafe behaviors. In: Automation in Construction, v. 82 (October 2017).
- (2018): Towards efficient and objective work sampling: Recognizing workers' activities in site surveillance videos with two-stream convolutional networks. In: Automation in Construction, v. 94 (October 2018).
- (2017): Visualization technology-based construction safety management: A review. In: Automation in Construction, v. 73 (January 2017).
- (2018): Wearable insole pressure system for automated detection and classification of awkward working postures in construction workers. In: Automation in Construction, v. 96 (December 2018).
Structurae cooperates with
