A new light ensemble deep-learning framework to detect fire

IF 1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
A. Alsheikhy, T. Shawly, Hossam Ahmed, Hassan Lahza
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引用次数: 0

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.
探测火灾的新型光集合深度学习框架
火灾会对土地、财产和人类造成毁灭性的破坏。许多国家因这些火灾遭受了巨大的经济损失。因此,有必要实施一个切实可行的解决方案,以有效和准确地点出火灾。深度学习算法和人工智能最近被应用于监控系统、经济学和检测等各个领域。提出了一种新的轻集成深度学习框架(NLEDLF)。该框架由两种深度学习技术组成,即新生成对抗网络(NGAN)和新卷积神经网络(NCNN)。将这两个工具与一些图像预处理方法结合到框架中,使用像素检测火灾。所提出的框架实现了合理的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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