UAVs have been deployed in various object tracking applications such as disaster
management, traffic monitoring, wildlife monitoring and crowd management. Recently …

This paper presents convolutional neural network (CNN)-based single object detection and
tracking algorithms. CNN-based object detection methods are directly applicable to static …

Deep learning methods have achieved the state-of-the-art performance of object detection
and tracking in natural images, such as keypoint-based detectors and appearance/motion …

Over the years, object tracking and detection has emerged as one of the most important
aspects of UAV applications such as surveillance, reconnaissance, etc. In our paper, we …

Single-object tracking, also known as visual tracking, on the drone platform attracts much
attention recently with various applications in computer vision, such as filming and …

Traditionally multi-object tracking and object detection are performed using separate
systems with most prior works focusing exclusively on one of these aspects over the other …

Tracking objects across multiple video frames is a challenging task due to several difficult
issues such as occlusions, background clutter, lighting as well as object and camera view …

In this paper, a real-time deep learning-based framework for detecting and tracking
Unmanned Aerial Vehicles (UAVs) in video streams captured by a fixed-wing UAV is …

Unmanned Aerial Vehicles (UAVs) gain popularity in a wide range of civilian and military
applications. Such emerging interest is pushing the development of effective collision …

Drones, or general UAVs, equipped with a single camera have been widely deployed to a
broad range of applications, such as aerial photography, fast goods delivery and most …