Wildfire Detection Using Computer Vision

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Date

2024-06

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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.

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Keywords

Wildfire Detection, Transfert Learning, Fusion technique, VGG16 Model

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