Deep learning applications for point clouds in the construction industry
Deep learning (DL) on point clouds holds significant potential in the construction industry,
yet no comprehensive review has thoroughly summarized its applications and shortcomings …
yet no comprehensive review has thoroughly summarized its applications and shortcomings …
A systematic review and evaluation of synthetic simulated data generation strategies for deep learning applications in construction
The integration of deep learning (DL) into construction applications holds substantial
potential for enhancing construction automation and intelligence. However, successful …
potential for enhancing construction automation and intelligence. However, successful …
Semantic enrichment of BIM with IndoorGML for quadruped robot navigation and automated 3D scanning
R Zhai, J Zou, VJL Gan, X Han, Y Wang… - Automation in …, 2024 - Elsevier
Planning scan routes with prior knowledge can improve scan data quality and
completeness. This paper presents a BIM-enabled approach to optimize quadruped robot …
completeness. This paper presents a BIM-enabled approach to optimize quadruped robot …
Dual hierarchical attention-enhanced transfer learning for semantic segmentation of point clouds in building scene understanding
L Zhang, Z Wei, Z Xiao, A Ji, B Wu - Automation in Construction, 2024 - Elsevier
Targeted to the challenge of indoor scene understanding for intelligent devices, this paper
question focuses on enhancing accuracy in semantic information extraction. A framework …
question focuses on enhancing accuracy in semantic information extraction. A framework …
Impact of color and mixing proportion of synthetic point clouds on semantic segmentation
Deep learning (DL)-based point cloud segmentation is essential for understanding built
environment. Despite synthetic point clouds (SPC) having the potential to compensate for …
environment. Despite synthetic point clouds (SPC) having the potential to compensate for …
Railway-Fastener Point Cloud Segmentation and Damage Quantification Based on Deep Learning and Synthetic Data Augmentation
W Wang, H Niu, S Qiu, J Wang, Y Luo… - Journal of Computing …, 2025 - ascelibrary.org
Accurate detection and quantification of damage to railway fasteners are crucial for ensuring
railway safety. The spatial damage defects caused by the complex shape of fasteners and …
railway safety. The spatial damage defects caused by the complex shape of fasteners and …