Cracks are a common defect in civil infrastructures, and their occurrence is often closely
related to structural loading conditions, material properties, design and construction, and …

The use of deep learning (DL) in civil inspection, especially in crack detection, has
increased over the past years to ensure long-term structural safety and integrity. To achieve …

Previous research has shown the high accuracy of convolutional neural networks (CNNs) in
asphalt and concrete crack detection in controlled conditions. Yet, human-like generalisation …

Cracks in concrete cause initial structural damage to civil infrastructures such as buildings,
bridges, and highways, which in turn causes further damage and is thus regarded as a …

Artificial intelligence (AI) provides advanced mathematical frameworks and algorithms for
further innovation and vitality of classical civil engineering (CE). Plenty of complex, time …

Deflection data provides important information about the mechanical characteristics and
structural health condition of bridges. The study presented here pertains to development of a …

Reinforced concrete (RC) columns may be exposed to blast loading. Assessment and
prediction of the damage condition and failure mode of RC columns are necessary for …

The integration of visible and thermal images has demonstrated the potential ability to
enhance crack segmentation accuracy. However, due to the intricate texture of masonry …

Deep learning-based methods, especially convolutional neural networks, have been
developed to automatically process the images of concrete surfaces for crack identification …

Fiber-reinforced geopolymer concrete has been attracting attention and interest worldwide
due to its sustainable properties. However, few studies have reported the pull-out behaviour …