Pavement, as a kind of common public transit infrastructure, plays an important part in the
daily passing and transportation-associated activities. The good conditions and smooth …

With the rapid growth in urban construction in Malaysia, road breakage has challenged
traditional manual inspection methods. In order to quickly and accurately detect the extent of …

Aiming at the demand for rapid detection of highway pavement damage, many deep
learning methods based on convolutional neural networks (CNNs) have been developed …

In recent years, graph-cut algorithms have been considered in image segmentation due to
their quality and computational load. Among these algorithms, radius-based function kernel …

Crack detection provides valuable information concerning the location, extent, type, and
severity for structural health monitoring of civil infrastructures. Due to the influence of uneven …

Road and bridge management are not an easy affair; Therefore, smart way is needed to
encourage easier, cost effective, and more efficient construction monitoring and …

In this work, we propose a road pavement damage detection deep learning model based on
feature points from a local minimum of grayscale. First, image blocks, consisting of the …

The appearance of cracks in underground infrastructures when presenting gives meaning of
weakening, Peru being a seismic country it's crucial to have the capability to locate the …

Frequent loading may cause pavement cracks, which have hidden dangers to vehicles and
pedestrians. Additionally, the cracks will also deteriorate over time thus the cracks should be …