Featured Application This paper proposes a deep-learning-based vehicle detection
technique that can achieve effective detection performance under extreme illumination …

Vision-based autonomous driving systems need to overcome many challenges at nighttime,
such as complicated illumination conditions, dazzle caused by headlamps, light refraction …

Vehicle detection from surveillance videos is of great significance for various Intelligent
Transportation System (ITS) applications. However, existing deep learning methods …

In this study, we propose a novel CLAHE-based nighttime image contrast enhancement
approach for vehicle detection under nighttime conditions, which improves the contrast of …

Numerous vehicle detection methods have been proposed to obtain trustworthy traffic data
for the development of intelligent traffic systems. Most of these methods perform sufficiently …

Vehicle detection and classification is a challenging move in the field of traffic management
and surveillance. With the rapid increase in the number of vehicles on roads, streets, and …

Existing night vehicle detection methods mainly detect vehicles by detecting headlights or
taillights. However, these features are adversely affected by the complex road lighting …

The recent boom of autonomous driving nowadays has made object detection in traffic
scenes a hot topic of research. Designed to classify and locate instances in the image, this is …

Autonomous driving systems in internet of vehicles (IoV) applications usually adopt a cloud
computing mode. In these systems, information got at the edge of the cloud computing …

For the past several decades, the number of vehicles has been increased for many times,
leading to a lot of traffic issues. The nighttime accident rate is much higher than that in …