Deep learning-based algorithms can provide state-of-the-art accuracy for remote sensing
technologies such as unmanned aerial vehicles (UAVs)/drones, potentially enhancing their …

Abstract UnmannedAerial Vehicles (UAVs), equipped with camera sensors can facilitate
enhanced situational awareness for many emergency response and disaster management …

The exponential growth of copter drone usage and the threats posed by drone users, such
as unauthorised imaging and filming in restricted areas, illegal surveillance, air collisions …

The Hogweed of Sosnowskyi (lat. Heracleum sosnówskyi) is poisonous for humans,
dangerous for farming crops, and local ecosystems. This plant is fast-growing and has …

Many applications utilizing Unmanned Aerial Vehicles (UAVs) require the use of computer
vision algorithms to analyze the information captured from their on-board camera. Recent …

Theability to efficiently plan and execute automated and precise search missions using
unmanned aerial vehicles (UAVs) during emergency response situations is imperative …

This paper proposed a lightweight, efficient Convolution Neural Network model for automatic
disaster recognition from aerial images. The model consists of a stack of convolutions and …

Natural disasters can be unpredictable and catastrophic. Even after the event, the
repercussions are prolonged due to the incompetence of disaster management strategies …

The ability to efficiently plan and execute search missions in challenging and complex
environments during natural and man-made disasters is imperative. In many emergency …

Deep Learning-based object detectors enhance the capabilities of remote sensing
platforms, such as Unmanned Aerial Vehicles (UAVs), in a wide spectrum of machine vision …