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http://dx.doi.org/10.13067/JKIECS.2017.12.2.331

Implementation of Image based Fire Detection System Using Convolution Neural Network  

Bang, Sang-Wan (Dept. of Computer Information, Songwon University)
Publication Information
The Journal of the Korea institute of electronic communication sciences / v.12, no.2, 2017 , pp. 331-336 More about this Journal
Abstract
The need for early fire detection technology is increasing in order to prevent fire disasters. Sensor device detection for heat, smoke and fire is widely used to detect flame and smoke, but this system is limited by the factors of the sensor environment. To solve these problems, many image-based fire detection systems are being developed. In this paper, we implemented a system to detect fire and smoke from camera input images using a convolution neural network. Through the implemented system using the convolution neural network, a feature map is generated for the smoke image and the fire image, and learning for classifying the smoke and fire is performed on the generated feature map. Experimental results on various images show excellent effects for classifying smoke and fire.
Keywords
Artificial Intelligence; Fire Detection; Deep Learning; Convolution Neural Network;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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