In urban environments there are daily issues of traffic congestion which city authorities need
to address. Realtime analysis of traffic flow information is crucial for efficiently managing …

Recently, intelligent video surveillance technologies using unmanned aerial vehicles
(UAVs) have been considerably increased in the transportation sector. Real time collection …

This paper presents an advanced urban traffic density estimation solution using the latest
deep learning techniques to intelligently process ultrahigh-resolution traffic videos taken …

The purpose of this paper is to provide a methodological framework to identify traffic
conditions based on non-calibrated video recordings captured from unmanned aerial …

The new development of the generation and a modern procedure called Industry 4.0 and its
advances in enormous information investigation and digital physical frameworks, regardless …

Alongside many traditional as well as novel applications, in the latest years, drones have
been widely adopted as remote sensing platforms for road traffic monitoring in urban areas …

Intelligent video surveillance technology has been increasingly used in the field of
transportation. Real-timely capturing traffic video data through the UAV is a new way to get …

With modern socio‐economic development, the number of vehicles in metropolitan cities is
growing rapidly. Therefore, obtaining real‐time traffic volume estimates has a very important …

Drone deployment has become crucial in a variety of applications, including solutions to
traffic issues in metropolitan areas and highways. On the other hand, data collected via …

In this paper, we propose a deep neural network-based method for estimating speed of
vehicles on roads automatically from videos recorded using unmanned aerial vehicle (UAV) …