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A new light ensemble deep-learning framework to detect fire

2023, vol.15 , no.4, pp. 37-48

Article [2023-04-04]

Authors
Ahmed Alsheikhy
Tawfeeq Shawly
Hossam E. Ahmed
Hassan Fareed M. Lahza
Abstract

Fires can cause devastating damage to lands, properties, and humans. Many countries suffer from huge financial losses due to these fires. Therefore, there is a need to implement a practical solution to spot fires effectively and accurately. Deep-learning algorithms and artificial intelligence have been deployed recently in various fields, such as monitoring systems, economics, and detection. This paper proposes a New Light Ensemble Deep-Learning Framework (NLEDLF). This framework consists of two deep-learning technologies, which are a New Generative Adversarial Network (NGAN) and a New Convolutional Neural Network (NCNN). These two tools are incorporated into the framework along with some image preprocessing methods to detect fires using pixels. The proposed framework achieves a reasonable.

Keywords

NGAN, NCNN, NLEDLF, fires, detection, light ensemble, framework

DOI

https://doi.org/10.59035/XNCU8652

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Citation of this article:

Ahmed Alsheikhy , Tawfeeq Shawly , Hossam E. Ahmed , Hassan Fareed M. Lahza . A new light ensemble deep-learning framework to detect fire. International Journal on Information Technologies and Security, vol.15 , no.4, 2023, pp. 37-48. https://doi.org/10.59035/XNCU8652