The 3D point cloud (3DPC) has significantly evolved and benefited from the advance of
deep learning (DL). However, the latter faces various issues, including the lack of data or …

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 …

Unprecedented growth in 3D reality-based capturing devices-such as Terrestrial Laser
Scanners (TLS) or Unnamed Aerial Vehicles (UAVs) equipped with high-resolution …

The rise of Industry 4.0 has led to a rapid increase in digitalization and industrial operations.
However, it has recently been deemed insufficient in fulfilling European objectives for 2030 …

Heritage buildings are increasingly vulnerable to environmental challenges like air pollution
and climate change. Traditional preservation methods primarily rely on periodic inspections …

The work developed aims to present an innovative methodology to execute the heritage
conservation processes in a collaborative and interdisciplinary Building Information …

The analysis and preservation of the cultural heritage sites are critical for maintaining their
historical and architectural integrity, as they can be damaged by various factors, including …

Point cloud semantic segmentation is a key step in the scan-to-HBIM process. In order to
reduce the information in the process of DGCNN, this paper proposes a Mix Pooling …

In recent years, the investigation and 3D documentation of architectural heritage has made
an efficient digitalization process possible and allowed for artificial intelligence post …

Construction risk management has evolved significantly by integrating artificial intelligence
(AI) technologies, particularly machine learning (ML), to enhance predictive capabilities …