Abstract Machine learning (ML) plays the core function to intellectualize the transportation
systems. Recent years have witnessed the advent and prevalence of deep learning which …

Abstract “Unmanned aerial vehicles”(UAVs) are now being used for a wide range of
surveillance applications. Specifically, the detection of on-ground vehicles from UAV images …

Advances in information and signal processing technologies have a significant impact on
autonomous driving (AD), improving driving safety while minimizing the efforts of human …

In recent years, various deep learning architectures have been proposed to solve complex
challenges (eg spatial dependency, temporal dependency) in traffic domain, which have …

The detection performance of small objects in remote sensing images has not been
satisfactory compared to large objects, especially in low-resolution and noisy images. A …

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 …

Analyzing videos and images captured by unmanned aerial vehicles or aerial drones is an
emerging application attracting significant attention from researchers in various areas of …

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 …

For assistance with grazing cattle management, we propose a cattle detection and counting
system based on Convolutional Neural Networks (CNNs) using aerial images taken by an …

Significant advancements and progress made in recent computer vision research enable
more effective processing of various objects in high-resolution overhead imagery obtained …