The developments in structural health monitoring techniques have led to the invention of
various sensors that can be effective damage indicator. Due to environmental or …

Computer vision‐based techniques were developed to overcome the limitations of visual
inspection by trained human resources and to detect structural damage in images remotely …

Deep learning‐based structural damage detection methods overcome the limitation of
inferior adaptability caused by extensively varying real‐world situations (eg, lighting and …

This paper aims to summarize central findings from a literature review and technical survey
on unmanned aerial vehicle (UAV) techniques for bridge inspection and damage …

This paper presents findings of delamination detection using infrared thermography (IRT) in
five in-service bridges using an unmanned aerial vehicle system. The authors have used …

Quantifying the condition of aging structures is important to verify structural integrity and long-
term reliability. Structural health monitoring plays a key role in the prevention of catastrophic …

Concrete damage images are essential for training deep learning-based damage detection
networks. Considering the manual collection of concrete damage images is time-consuming …

Infrastructure defect detection solutions based on computer vision have recently emerged as
powerful tools with applications in both traditional inspection practices, as well as robotic …

Bridge infrastructure asset management system is a prevailing approach toward having an
effective and efficient procedure for monitoring bridges through their different development …

Although crack inspection is a routine practice in civil infrastructure management (especially
for highway bridge structures), it is time‐consuming and safety‐concerning to trained …