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 …

Advent of computationally efficient smartphones, inexpensive high‐resolution cameras,
drones, and robotic sensors has brought a new era of next‐generation intelligent monitoring …

The widespread application of sophisticated structural health monitoring systems in civil
infrastructures produces a large volume of data. As a result, the analysis and mining of …

This paper reports the application of deep learning for implementing the anomaly detection
of defects on concrete structures, so as to facilitate the visual inspection of civil infrastructure …

This paper proposed a modified faster region‐based convolutional neural network (faster R‐
CNN) for the multitype seismic damage identification and localization (ie, concrete cracking …

This research assesses the performance of two deep learning models, SAM and U-Net, for
detecting cracks in concrete structures. The results indicate that each model has its own …

Routine inspection and maintenance are critical for the proper functioning of civil
infrastructures such as bridges, pavements and underground structures. Civil infrastructures …

Manual visual inspection is the most common means of assessing the condition of civil
infrastructure in the United States, but can be exceedingly laborious, time-consuming, and …

Classifying concrete defects during a bridge inspection remains a subjective and laborious
task. The risk of getting a false result is approximately 50% if different inspectors assess the …

This research proposes an approach for vision-based autonomous navigation planning of
unmanned aerial vehicles for the collection of images suitable for the rapid post-earthquake …