Road surfaces suffer from sources of deterioration, such as weather conditions, constant
usage, loads, and the age of the infrastructure. These sources of decay generate anomalies …

Abstract Mobile Edge Computing (MEC) is a modern paradigm that involves moving
computing and storage resources closer to the network edge, reducing latency, and …

Owing to the development of convolutional neural networks (CNNs), the detection of defects
on rail surfaces has significantly improved. Although existing methods achieve good results …

This systematic literature review provides a structured and detailed overview of research on
anomaly detection for connected and autonomous vehicles, focusing on the Artificial …

Road ponding, a prevalent traffic hazard, poses a serious threat to road safety by causing
vehicles to lose control and leading to accidents ranging from minor fender benders to …

Salient object detection is a challenging task in computer vision and has been used to
extract valuable information from many real scenarios. The graph-based detection approach …

This systematic review focuses on anomaly detection for connected and autonomous
vehicles. The initial database search identified 2160 articles, of which 203 were included in …

Monitoring road pavement conditions is vital to prevent harm or accidents to vehicles and
people, and it is a crucial governmental task. Some Artificial Intelligence (AI) based systems …

To improve the intelligent driving abilities about the day-night situation awareness and large
airspace real-time acquisition, we employ a forward-looking omnidirectional infrared …

Powerful navigation and safety systems are vital to ensuring autonomous (DV) or semi-
autonomous vehicles continue well in varied environmental conditions. However, in such a …