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

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

Nighttime vehicle detection plays an essential role in Automatic Driving System (ADS) and
Driver Assistance System (DAS). However, the visual features of the vehicle at night are …

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

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 …

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

Vehicle detection at nighttime plays a vital role in reducing the incidence of night traffic
accidents. In order to further improve the accuracy of nighttime vehicle detection, and to be …

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 …

Despite significant progress in vision-based detection methods, the task of detecting traffic
objects at night remains challenging. Visual information of medium and small stationary …