This paper presented an exhaustive survey on the security and privacy issues of drones.
These security concerns were thoroughly dissected, particularly the aspect of cybersecurity …

Unmanned aerial vehicles (UAVs) have emerged as a rapidly growing technology seeing
unprecedented adoption in various application sectors due to their viability and low cost …

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

Unmanned aerial vehicles or drones quickly became cheaper, becoming more advanced
and affordable to the general public. And the ease of control made them popular among …

This paper investigates the problem of classification of unmanned aerial vehicles (UAVs)
from radio frequency (RF) fingerprints at the low signal-to-noise ratio (SNR) regime. We use …

Since the beginning of the COVID-19 pandemic, the demand for unmanned aerial vehicles
(UAVs) has surged owing to an increasing requirement of remote, noncontact, and …

Unmanned Aerial Vehicle (UAV) detection and classification methods include the use of
audio, video, thermal, RADAR and radio frequency (RF) signals. RF signals have the ability …

This study proposes a high-accuracy two-stage trilateration method that enables real-time
positioning in global position system (GPS)-denied areas, such as unmanned aerial …

Small unmanned aerial systems (UASs) present many potential solutions and
enhancements to industry today but equally pose a significant security challenge. We only …

Affected by the nondeterministic nature of flight trajectories, the external environment, and
airport operational conditions, the prediction of the estimated time of arrival (ETA) is one of …