Modern deep learning methods for forest fire detection and prediction based on drone data

Abstract

Modern deep learning methods for forest fire detection and prediction based on drone data

Vegera D.V., Zabavin A.S.

Incoming article date: 18.11.2025

The article discusses modern approaches to forecasting and detecting forest fires using machine learning technologies and remote sensing data. Special attention is paid to the use of computer vision algorithms, such as convolutional neural networks and transformers, to detect and segment fires in images from unmanned aerial vehicles. The high efficiency of hybrid architectures and lightweight models for real-time operation is noted.

Keywords: forest fires, forecasting, unmanned aerial vehicles, deep learning, convolutional neural networks, transformers, image segmentation