Civil infrastructure (eg, buildings, roads, underground tunnels) could lose its expected
physical and functional conditions after years of operation. Timely and accurate inspection …

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

Persistent cracking and progressive damage can weaken the operational performance of
structures such as bridges, dams, and concrete buildings. Consequently, research into …

Accurate pavement surface crack detection is essential for pavement assessment and
maintenance. This study aims to improve pavement crack detection under noisy conditions …

The conventional method of manually verifying the quality of tiled sidewalks is laborious,
because of the time-consuming identification of cracks from numerous grid-like elements of …

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 …

Annually, millions of dollars are spent to carry out defect detection in key infrastructure
including roads, bridges, and buildings. The aftermath of natural disasters like floods and …

Cracks are important indicators of pavement structural and operational conditions. Early
pavement crack detection and treatments can help extend pavement service life, reduce fuel …

Cracks are typical line structures that are of interest in many computer-vision applications. In
practice, many cracks, eg, pavement cracks, show poor continuity and low contrast, which …

Computer vision techniques, in conjunction with acquisition through remote cameras and
unmanned aerial vehicles (UAVs), offer promising non-contact solutions to civil infrastructure …