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Albeaino, G, Brophy, P, Jeelani, I, Gheisari, M and Issa, R R A (2023) Impact of drone presence on construction individuals working at heights. Journal of Construction Engineering and Management, 149(11).
Chadee, A A, Martin, H, Chadee, X T, Bahadoorsingh, S and Olutoge, F (2023) Root cause of cost overrun risks in public sector social housing programs in sids: Fuzzy synthetic evaluation. Journal of Construction Engineering and Management, 149(11).
Duan, P, Zhou, J and Goh, Y M (2023) Safety risk diagnosis based on motion trajectory for construction workers: An integrated approach. Journal of Construction Engineering and Management, 149(11).
Erk, E Y, Budayan, C, Koc, K and Tokdemir, O B (2023) Value creation in PPP projects undertaken in the Turkish healthcare industry. Journal of Construction Engineering and Management, 149(11).
Hsu, C L, Wang, J T and Hou, H Y (2023) A blockchain-based parametric model library for knowledge sharing in building information modeling collaboration. Journal of Construction Engineering and Management, 149(11).
Lim, H W and Francis, V (2023) A conceptual model of cognitive and behavioral processes affecting mental health in the construction industry: A systematic review. Journal of Construction Engineering and Management, 149(11).
Mostofi, F, Toǧan, V, Başaǧa, H B, Çltlpltloǧlu, A and Tokdemir, O B (2023) Multiedge graph convolutional network for house price prediction. Journal of Construction Engineering and Management, 149(11).
Tang, Y and Yao, H (2023) Watch out for the hidden costs of subcontracting in construction projects: The impacts of subcontractor dispersion. Journal of Construction Engineering and Management, 149(11).
Wang, D, Huang, R, Qiao, Y, Sheng, Z, Li, K and Zhao, L (2023) How perceived leader-member exchange differentiation affects construction workers' safety citizenship behavior: Organizational identity and felt safety responsibility as mediators. Journal of Construction Engineering and Management, 149(11).
Wang, S, Kim, M, Hae, H, Cao, M and Kim, J (2023) The development of a rebar-counting model for reinforced concrete columns: Using an unmanned aerial vehicle and deep-learning approach. Journal of Construction Engineering and Management, 149(11).
- Type: Journal Article
- Keywords: deep learning; faster r-cnn; image augmentation; rebar counting; reinforced concrete structure; unmanned aerial vehicle
- ISBN/ISSN: 0733-9364
- URL: http://doi.org/10.1061/JCEMD4.COENG-13686
- Abstract:
Inspecting the number of rebars in each column of a reinforced concrete (RC) structure is a significant task that must be undertaken during the rebar inspection process. Conventionally, counting the rebars has relied on a manual inspection carried out by visiting inspectors. However, this approach is very time-consuming, labor-intensive, and poses a potential safety risk. Previous studies have focused on the applications of counting the rebars for a production line and/or warehouse, using vision-based methods. Therefore, this study aims to propose an innovative approach incorporating the use of an unmanned aerial vehicle (UAV) on real construction sites to count the rebars automatically. For analyzing the images, robust object detection methods based on deep learning (Faster R-CNN, R-FCN, SSD 300, SSD500, YOLOv5, and YOLOv6) were developed. A total of 384 models generated from six different methods were trained and implemented using data sets based on the original and augmented images with adjustments made for the hyperparameters. In a test, the best optimized model based on Faster R-CNN produced an accuracy of 94.61% at AP50. In addition, video testing demonstrated a coverage of up to 32 frames per second in the experimental environment, suggesting that this method has potential for real-time application.
Wang, Z, He, Q, Locatelli, G, Wang, G and Li, Y (2023) Exploring environmental collaboration and greenwashing in construction projects: Integrative governance framework. Journal of Construction Engineering and Management, 149(11).
Watton, J, Unterhitzenberger, C, Locatelli, G and Invernizzi, D C (2023) The cost drivers of infrastructure projects: Definition, classification, and conceptualization. Journal of Construction Engineering and Management, 149(11).
Wu, H, Han, Y, Zhang, M, Abebe, B D, Legesse, M B and Jin, R (2023) Identifying unsafe behavior of construction workers: A dynamic approach combining skeleton information and spatiotemporal features. Journal of Construction Engineering and Management, 149(11).
Wu, L, Mohamed, E, Jafari, P and Abourizk, S (2023) Machine learning-based Bayesian framework for interval estimate of unsafe-event prediction in construction. Journal of Construction Engineering and Management, 149(11).
Wu, S, Yu, L, Cao, T, Yuan, C and Du, Y (2023) How dependence asymmetry and explicit contract shape contractor-subcontractor collaboration: A psychological perspective of fairness. Journal of Construction Engineering and Management, 149(11).
You, H, Xu, F and Du, J (2023) Improved boundary identification of stacked objects with sparse lidar augmentation scanning. Journal of Construction Engineering and Management, 149(11).
Zheng, X, Chen, J, Xia, B, Skitmore, M and Zeng, S (2023) Understanding the megaproject social responsibility network among stakeholders: A reciprocal-exchange perspective. Journal of Construction Engineering and Management, 149(11).
Zhou, Q, Deng, X, Hwang, B G, Mahmoudi, A and Liu, Y (2023) Integrating the factors affecting knowledge transfer within international construction projects: Individual and team perspectives. Journal of Construction Engineering and Management, 149(11).