Abstract Convolutional Neural Networks (CNN) have immense potential to solve a broad
range of computer vision problems. It has achieved encouraging results in numerous …

As technology continues to develop, computer vision (CV) applications are becoming
increasingly widespread in the intelligent transportation systems (ITS) context. These …

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

Routine visual inspection is essential to maintain adequate safety and serviceability of civil
infrastructures. Computer vision and machine learning based software techniques are …

This study investigates the semantic segmentation of common concrete defects when using
different imaging modalities. One pre-trained Convolutional Neural Network (CNN) model …

The concrete aging problem has gained more attention in recent years as more bridges and
tunnels in the United States lack proper maintenance. Though the Federal Highway …

Conventional methods for visual assessment of civil infrastructures have certain limitations,
such as subjectivity of the collected data, long inspection time, and high cost of labor …

We investigate the capabilities of transfer learning in the area of structural health monitoring.
In particular, we are interested in damage detection for concrete structures. Typical image …

This paper summarizes the results of traditional image processing algorithms for detection of
defects in concrete using images taken by Unmanned Aerial Systems (UASs). Such …

This study aims to investigate the current knowledge of unmanned aerial vehicle (UAV)‐
based simultaneous localization and mapping (SLAM) in outdoor environments and to …