Wildfire Detection Using Computer Vision
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Date
2024-06
Journal Title
Journal ISSN
Volume Title
Publisher
UNIVERSITY OF MOHAMED BOUDIAF – MSILA, FACULTY OF MATHEMATICS AND COMPUTER SCIENCE, DEPARTMENT OF COMPUTER SCIENCE
Abstract
This work aims to enhance early and real-time wildfire detection utilizing computer vision
and transfer learning techniques, specifically employing the VGG16 model. We developed
two models, the first using only RGB images, achieving an accuracy of 88%, representing a
4% improvement over previously existing models. The second model utilize fusion technique,
integrates both RGB and thermal images, attaining a remarkable 99% accuracy. Additionally,
prototypes for future web and mobile applications have been created to facilitate real-time
wildfire detection and response.
Description
Keywords
Wildfire Detection, Transfert Learning, Fusion technique, VGG16 Model