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 …

Unmanned Aerial Vehicles (UAVs) have immense potential to enhance Intelligent Transport
Systems (ITS) by aiding in real-time traffic monitoring, emergency response, and …

Owing to effective and flexible data acquisition, unmanned aerial vehicles (UAVs) have
recently become a hotspot across the fields of computer vision (CV) and remote sensing …

This study highlights the evolving landscape of object detection methodologies,
emphasizing the superiority of deep learning-based approaches over traditional methods …

Video streaming-based real-time vehicle identification and license plate recognition systems
are challenging to design and deploy in terms of real-time processing on edge, dealing with …

Unmanned aerial vehicles (UAVs) equipped with computer vision capabilities have been
widely utilized in several remote sensing applications, such as precision agriculture …

Foreign object debris (FOD) can critically damage aircraft engines as well as injure
personnel in an airport environment. Airfield inspectors routinely inspect runways for the …

Aerial vehicle detection has significant applications in aerial surveillance and traffic control.
The pictures captured by the UAV are characterized by many tiny objects and vehicles …

Systems must be capable of detecting and tracking autonomous vehicles for intelligent
management and control of transportation. Even though several methods are used to create …

In this paper, we propose an original deep learning framework for the automated counting
and geolocation of palm trees from aerial images using convolutional neural networks. For …