As technology continues to develop, computer vision (CV) applications are becoming
increasingly widespread in the intelligent transportation systems (ITS) context. These …

The intelligent detection of pavement distress using deep learning methods has consistently
been a hotspot in pavement maintenance. This paper aims to offer new insights to promote …

The recent advancements in deep convolutional neural networks have shown significant
promise in the domain of road scene parsing. Nevertheless, the existing works focus …

Potholes pose a significant problem for road safety and infrastructure. They can cause
damage to vehicles and present a risk to pedestrians and cyclists. The ability to detect …

Potholes and other road surface damages pose significant risks to vehicles and traffic safety.
The current methods of in situ visual inspection for potholes or cracks are inefficient, costly …

Roughness is widely used as a primary measure of pavement condition. It is also the key
indicator of the riding quality and serviceability of roads. The high demand for roughness …

This paper addresses the growing demands for safety and comfort in intelligent robot
systems, particularly autonomous vehicles, where road conditions play a pivotal role in …

Poorly maintained roads can cause lethal automobile accidents in various ways. Thus,
detecting and reporting damaged parts of roads is one of the most crucial road maintenance …

With the recent advancements in artificial intelligence, there is a growing expectation that
fully autonomous driving vehicles will soon become a reality, leading to significant societal …

Stereo matching is the process of generating dense correspondences in stereo images in
order to create a disparity map for depth perception. Stereo matching is different from flow …