基于卷积神经网络图像处理技术的火灾探测

Raam Pujangga Sadewa, Budhi Irawan, C. Setianingsih
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引用次数: 17

摘要

火是一种火焰,无论大小,都是不受欢迎的地点、情况和时间。一般来说,每个地方都有可能发生火灾。但在这个时候,烟雾传感器是最广泛使用的设备来探测火灾。烟雾传感器只有在火势较大时才能探测到火灾。所以需要一个系统来探测早期火灾。本文以笔记本电脑和网络摄像头为主要设备,设计了一种基于图像的火灾报警系统。使用卷积神经网络(CNN)识别火灾的方法。该系统的准确率为92%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fire Detection Using Image Processing Techniques with Convolutional Neural Networks
Fire is a flame, whether it is small or large, an undesirable place, situation and time. In general, every place has the potential to experience a fire. But at this time, the smoke sensors are the most widely used devices to detect fires. Where the smoke sensors can only detect fires if the fire is large. So that a system is needed to detect early fires. In this paper, an image-based fire alarm system is designed, using a laptop and webcam as the main equipment. The method for using Convolutional Neural Networks (CNN) to identify fire. The system created has an accuracy rate of 92%.
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