The manual creation of digital models of existing buildings for operations and maintenance
is difficult and time-consuming. Machine learning and deep learning techniques have …

Abstract Graph Neural Networks (GNNs) have emerged as a promising solution for
effectively handling non-Euclidean data in construction, including building information …

Automatic comparison of time-variant BIM models facilitates value-added applications
during the building life cycle. This paper addresses a solution capable of exploring changes …

Deep learning-based object detection (DLOD) methods are crucial in assisting dynamic
construction site management (DCSM) but have not been systematically studied. This paper …

This study proposes a feature relationship algorithm (FRA) to reconstruct three-dimensional
wireframes of objects with non-Manhattan shapes using segmented point clouds. Instead of …

The creation of 2D–3D architectural vector drawings constitutes a manual, labor-intensive
process. The scientific community has not provided an automated approach for the …

摘要點雲結構化為被廣泛研究之課題, 現今演算法的適應性及成果的細緻度仍有改善的空間.
本研究提出特徵關係(Feature Relationship Algorithm, FRA) 演算法, FRA …

RESUMO A preservação do patrimônio arquitetônico cultural é uma questão relevante
devido aos problemas de deterioração e destruição enfrentados por essas estruturas. A …

Onsite activities of modular integrated construction (MiC) mainly involve repetitive module
installation processes. Automatic three-dimensional module detection (3DMD) can facilitate …