In this paper, we address the problem of forest fires' early detection and segmentation in
order to predict their spread and help with fire fighting. Techniques based on Convolutional …

Wildfire, also known as forest fire, is a common natural or man-made disaster that has
caused devastation to both man-made structures and natural ecosystems throughout the …

In the last decade, researchers have focused more on deep convolutional neural networks
(CNNs) than other machine learning algorithms for object detection, localization …

Unmanned Aerial Vehicles (UAVs), which can provide an aerial view for fast responding in
large-scale zones of disaster, are recently utilized for forest fire monitoring. In this paper, one …

Abstract In recent years, Unmanned Aerial Vehicles (UAVs) have grown and increased in
applications because of computational simplicity and adaptive control capacity with strong …

The early detection of wildfires is a crucial challenge in environmental monitoring, pivotal for
effective disaster management and ecological conservation. Traditional detection methods …

This paper introduces a location–allocation model to support environmental emergency
response strategic planning using a drone-based network. Drones are used to verify …

Convolutional neural networks (CNNs) have shown success in picture classification and
other computer vision issues. The use of CNN in the fire recognition technique will greatly …

In recent years, autonomous vehicles have shown to be increasingly useful in performing
complex tasks in cooperative scenarios. The Platform, a multi-agent distributed system …

Convolutional neural networks (CNNs) have yielded stateof-threat performance in image
classification and other computer vision tasks. Their application in fire detection systems will …