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Unmanned Aerial Vehicles (UAVs) are one of the most revolutionary inventions of 21st century. At the core of a UAV lies the central processing system that uses wireless signals to control their movement. The most popular UAVs are…
Landing safely in crowded urban environments remains an essential yet challenging endeavor for Unmanned Aerial Vehicles (UAVs), especially in emergency situations. In this work, we propose a risk-aware approach that harnesses semantic…
This paper describes how advanced deep learning based computer vision algorithms are applied to enable real-time on-board sensor processing for small UAVs. Four use cases are considered: target detection, classification and localization,…
The emerging drone aerial survey has the advantages of low cost, high efficiency, and flexible use. However, UAVs are often equipped with cheap POS systems and non-measurement cameras, and their flight attitudes are easily affected. How to…
Cellular-based Unmanned Aerial Vehicle (UAV) systems are a promising paradigm to provide reliable and fast Beyond Visual Line of Sight (BVLoS) communication services for UAV operations. However, such systems are facing a serious GPS…
Object detection from Unmanned Aerial Vehicles (UAVs) is of great importance in many aerial vision-based applications. Despite the great success of generic object detection methods, a significant performance drop is observed when applied to…
The development of the low-altitude economy has led to a growing prominence of uncrewed aerial vehicle (UAV) safety management issues. Therefore, accurate identification, real-time localization, and effective countermeasures have become…
Multi-object tracking (MOT) is a crucial component of situational awareness in military defense applications. With the growing use of unmanned aerial systems (UASs), MOT methods for aerial surveillance is in high demand. Application of MOT…
Unmanned Aerial Vehicles (drones) are emerging as a promising technology for both environmental and infrastructure monitoring, with broad use in a plethora of applications. Many such applications require the use of computer vision…
In this paper, we present an on-board vision-based approach for avoidance of moving obstacles in dynamic environments. Our approach relies on an efficient obstacle detection and tracking algorithm based on depth image pairs, which provides…
The integration of unmanned aerial vehicles (UAVs) into shared airspace for beyond visual line of sight (BVLOS) operations presents significant challenges but holds transformative potential for sectors like transportation, construction,…
This paper presents a comprehensive review of recent advancements in image processing and deep learning techniques for pavement distress detection and classification, a critical aspect in modern pavement management systems. The conventional…
An onboard target detection, tracking and avoidance system has been developed in this paper, for low-cost UAV flight controllers using AI-Based approaches. The aim of the proposed system is that an ally UAV can either avoid or track an…
Visual perception is an important component for autonomous navigation of unmanned surface vessels (USV), particularly for the tasks related to autonomous inspection and tracking. These tasks involve vision-based navigation techniques to…
In this paper, we present our deep learning-based human detection system that uses optical (RGB) and long-wave infrared (LWIR) cameras to detect, track, localize, and re-identify humans from UAVs flying at high altitude. In each spectrum, a…
The use of unmanned aerial vehicles (UAVs) for different applications has increased many folds in recent years. The UAVs are expected to change the future air operations. However, there are instances where the UAVs can be used for malicious…
Obstacle avoidance for small unmanned aircraft is vital for the safety of future urban air mobility (UAM) and Unmanned Aircraft System (UAS) Traffic Management (UTM). There are many techniques for real-time robust drone guidance, but many…
Anomaly detection is a key goal of autonomous surveillance systems that should be able to alert unusual observations. In this paper, we propose a holistic anomaly detection system using deep neural networks for surveillance of critical…
This paper investigates the problem of traffic surveillance using an unmanned aerial vehicle (UAV) and proposes a domain-knowledge-aided airborne ground moving targets tracking algorithm. To improve the accuracy of multiple targets…
Research in visual anomaly detection draws much interest due to its applications in surveillance. Common datasets for evaluation are constructed using a stationary camera overlooking a region of interest. Previous research has shown…