A number of image processing techniques (IPTs) have been implemented for detecting civil
infrastructure defects to partially replace human‐conducted onsite inspections. These IPTs …

This paper compares the performance of common edge detectors and deep convolutional
neural networks (DCNN) for image-based crack detection in concrete structures. A dataset of …

Cracks are a potential threat to the safety and endurance of civil infrastructures, and
therefore, careful and regular structural crack inspection is needed during their long-term …

With the growing number of aging infrastructure across the world, there is a high demand for
a more effective inspection method to assess its conditions. Routine assessment of structural …

The damage investigation and inspection methods for infrastructures performed in small-
scale (type III) facilities usually involve a visual examination by an inspector using surveying …

This study proposed a semi-automated system for crack detection and quantification, based
on the combination of a trained convolutional neural network (CNN) and a developed …

This paper proposes a customized convolutional neural network for crack detection in
concrete structures. The proposed method is compared to four existing deep learning …

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

With the rapid increase of ageing infrastructures worldwide, effective and robust inspection
techniques are highly demanding to evaluate structural conditions and residual lifetime. The …

Crack detection is important for the inspection and evaluation during the maintenance of
concrete structures. However, conventional image‐based methods need extract crack …