This paper addresses the problem of car detection from aerial images using Convolutional
Neural Networks (CNNs). This problem presents additional challenges as compared to car …

In this paper, we address the problem of car detection from aerial images using
Convolutional Neural Networks (CNN). This problem presents additional challenges as …

Unmanned Aerial Vehicles are increasingly being used in surveillance and traffic monitoring
thanks to their high mobility and ability to cover areas at different altitudes and locations …

To solve real-life problems for different smart city applications, using deep Neural Network,
such as parking occupancy detection, requires fine-tuning of these networks. For large …

With the application of UAVs in intelligent transportation systems, vehicle detection for aerial
images has become a key engineering technology and has academic research significance …

Automated driving and vehicle safety systems need object detection. It is important that
object detection be accurate overall and robust to weather and environmental conditions …

Vehicle detection from unmanned aerial vehicle (UAV) imagery is one of the most important
tasks in a large number of computer vision-based applications. This crucial task needed to …

This paper presents deep learning-based YOLO (You only look once), for the detection of an
unmanned aerial vehicle (UAV). In common practice, the creation of own data set is an …

Abstract Nowadays, Unmanned Aerial Vehicles (UAVs) have become useful for various civil
applications, such as traffic monitoring and smart parkings, where real-time vehicle detection …

Deep learning-based classification and detection algorithms have emerged as a powerful
tool for vehicle detection in intelligent transportation systems. The limitations of the number …