A systematic review and evaluation of synthetic simulated data generation strategies for deep learning applications in construction

L Xu, H Liu, B ** using feature fusion and large vision models
K Sun, Z Shao, YM Goh, J Tian, VJL Gan - Automation in Construction, 2025 - Elsevier
Although poor housekee** leads to construction accidents, there is limited technological
research on it. Existing methods for detecting poor housekee** face many challenges …

Deep learning without human labeling for on-site rebar instance segmentation using synthetic BIM data and domain adaptation

TW Huang, YH Chen, JJ Lin, CS Chen - Automation in Construction, 2025 - Elsevier
On-site rebar inspection is crucial for structural safety but remains labor-intensive and time-
consuming. While deep learning presents a promising solution, existing research often …

Hybrid Data Augmentation for Enhanced Crack Detection in Building Construction

SM Choi, HS Cha, S Jiang - Buildings, 2024 - mdpi.com
Quality management in construction projects necessitates early defect detection, traditionally
conducted manually by supervisors, resulting in inefficiencies and human errors. Addressing …

[HTML][HTML] Generating Synthetic Images for Construction Machinery Data Augmentation Utilizing Context-Aware Object Placement

Y Lu, B Liu, W Wei, B **ao, Z Liu, W Li - Developments in the Built …, 2025 - Elsevier
Dataset is an essential factor influencing the accuracy of computer vision (CV) tasks in
construction. Although image synthesis methods can automatically generate substantial …

A Voxel-Based 3D reconstruction and action recognition method for construction workers

J Zhang, D Wang, X An, M Lv, D Chen, A Sun - Advanced Engineering …, 2025 - Elsevier
Workers are critical yet unpredictable elements on construction sites, with their actions
significantly impacting safety and productivity. Recognizing these actions is essential for …