Structural health monitoring at local and global levels using computer vision technologies
has gained much attention in the structural health monitoring community in research and …

Abstract Applications of Machine Learning (ML) algorithms in Structural Health Monitoring
(SHM) have become of great interest in recent years owing to their superior ability to detect …

With recent advances in non-contact sensing technology such as cameras, unmanned aerial
and ground vehicles, the structural health monitoring (SHM) community has witnessed a …

Data-driven methods in structural health monitoring (SHM) is gaining popularity due to
recent technological advancements in sensors, as well as high-speed internet and cloud …

Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …

Physics‐informed neural networks (PINNs) are a class of deep neural networks that are
trained, using automatic differentiation, to compute the response of systems governed by …

Computer vision techniques, in conjunction with acquisition through remote cameras and
unmanned aerial vehicles (UAVs), offer promising non-contact solutions to civil infrastructure …

Computer vision-based crack analysis for civil infrastructure has become popular to
automatically process inspection imaging data for crack detection, localisation and …

This paper presents a comprehensive disassembly sequence planning (DSP) algorithm in
the human–robot collaboration (HRC) setting with consideration of several important factors …

In the past two decades, structural health monitoring (SHM) systems have been widely
installed on various civil infrastructures for the tracking of the state of their structural health …