Ensuring traffic safety is crucial, which necessitates the detection and prevention of road
surface defects. As a result, there has been a growing interest in the literature on the subject …

Road surface crack detection methods using vehicle-mounted images have gained
substantial attention recently. Notably, YOLO-based techniques have exhibited effectiveness …

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 …

Abstract The Multi-fusion U-Net network based on U-Net is proposed to attain pixel-level
detection of sealed cracks. The multi-fusion module, dual attention mechanism, and Atrous …

Autonomous vehicles can transform the transportation sector by offering a safer and more
effective means of travel. However, the success of self-driving cars depends on their ability …

Road surfaces are highly affected by climatic changes which caused potholes and cracks.
Maintenance of the road is a need-of-the-hour process for preventing the physical damage …

Deep learning (DL) semantic segmentation of tunnel point cloud shows an efficient path for
applications related to subway tunnel scenes, such as health inspection and building …

Road damage detection is essential to the maintenance and management of roads. The
morphological road damage contains a large number of multi-scale features, which means …

As the global population increases, so does the number of vehicles on our roads, which
makes maintenance of the road infrastructure critical for safe and efficient transportation. A …

We propose CurveML, a benchmark for evaluating and comparing methods for the
classification and identification of plane curves represented as point sets. The dataset is …