Crack inspection is a crucial but labor-intensive work of maintenance for in-service bridges.
Recently, the development of fully convolutional network (FCN) provides pixel-wise …

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

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 …

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

Regular inspections of bridge substructures are very important for evaluating bridge health,
since early detection and assessment offer the best chances of bridge repair. However, the …

The spatial characteristics of cracks are significant indicators to assess and evaluate the
health of existing buildings and infrastructures. However, the current manual crack …

Cracks are one of the most serious defects that threaten the safety of bridges. In order to
detect different forms of cracks in different collection environments quickly and accurately …

Cracks in civil structures are important signs of structural degradation and may even indicate
the inception of catastrophic failure. Image‐based crack detection has been attempted in …

Crack detection plays a vital role in concrete surface maintenance. Deep-learning-based
methods have achieved state-of-the-art results. However, these methods have some …

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 …