In recent years deep-learning techniques have been developed and applied to inspect
cracks in RC structures. The accuracy of these techniques leads to believe that they may …

At present, a number of computer vision-based crack detection techniques have been
developed to efficiently inspect and manage a large number of structures. However, these …

This work presents the combination of Deep-Learning (DL) and image processing to
produce an automated cracks recognition and defect measurement tool for civil structures …

The inspection of defects in concrete infrastructure is a costly and time-consuming task.
Many image processing techniques (IPTs) have been proposed to replace manual …

Crack detection has vital importance for structural health monitoring and inspection of
buildings. The task is challenging for computer vision methods as cracks have only low-level …

Ensuring the structural integrity of civil infrastructures is critical, given the potential hazards
presented by cracks. Traditional manual inspections, though common, often face challenges …

In this paper, a deep learning approach synergetically to a laser scanning process are
employed for the visual detection and accurate description of concrete defects in tunnels …

Crack formation is one of the first indicators of degradation of the concrete structure.
Therefore, they must be detected early to take the necessary precautions to avoid further …

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

Civil infrastructures, such as tunnels and bridges, are directly related to the overall economic
and demographic growth of countries. The aging of these infrastructures increases the …