Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …

Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …

To date, data mining (DM) techniques, ie artificial intelligence, machine learning, and
statistical methods have been utilized in a remarkable number of structural health monitoring …

Photographs of bridges can reveal considerable technical information such as the part of the
structure that is damaged and the type of damage. Maintenance and inspection engineers …

Ground‐penetrating radar (GPR) is widely used to determine the location of buried pipes
without excavation, and machine learning has been researched to automatically identify the …

As the most common road distress, cracks have a substantial influence on the integrity of
pavement structures. Accurate identification of crack existence and quantification of crack …

Due to their wide applicability in inspection of concrete structures, there is considerable
interest in the development of automated crack detection method by image processing …

The development of effective life cycle management strategies for transport infrastructure
assets is of importance for meeting the defined public policies and levels of service. In the …

Abstract Machine learning models have been developed to perform damage detection using
images to improve bridge inspection efficiency. However, in damage detection using images …

Accurate corrosion assessment of reinforced concrete (RC) structures is expected to
improve the service life and durability of structures. However, traditional evaluation methods …