Light-weight convolutional neural network for fire detection

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Date

2021-07

Journal Title

Journal ISSN

Volume Title

Type

Article

Publisher

Institute of Electrical and Electronics Engineers Inc.

Series Info

ICEEM 2021 - 2nd IEEE International Conference on Electronic Engineering.;3 July 2021 Article number 94803782nd IEEE International Conference on Electronic Engineering, ICEEM 2021

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Abstract

Fire disasters damage the economy across the globe and cause many casualties among civilians and firefighters. In this paper, a deep learning architecture based on the convolutional neural network (CNN) is proposed to detect fires efficiently. We trained the network on 9247, picked high-resolution images containing fire and other ones without any fire, and investigated the effect of CNN depth on its classification accuracy. In this proposed work, we achieved 98% accuracy on the testing set, which is so far better than the previous state-of-the-art and will eventually minimize fire disasters and reduce the damage caused by human resources. © 2021 IEEE.

Description

Scopus

Keywords

Classification, Computer Vision, Convolution Neural Network (CNN), Fire Detection, Supervised Learning

Citation