利用计算机视觉和机器学习的火灾报警检测进展:文献综述

M. F. Ridhani, W. Mahmudy
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引用次数: 0

摘要

火灾是威胁公共安全和社会发展的最常见且日益严重的突发事件之一。这可能会造成重大的生命损失和损坏。火灾探测系统在火灾的早期探测中发挥着重要作用。本研究的目的是对该领域的最新文献进行简要调查,为研究人员开发具有计算机视觉和机器学习方法的火灾报警检测系统提供基础。计算机视觉和机器学习方法因其优点而广受欢迎并得到了广泛的研究。火灾探测系统的主要挑战是误报率高和响应时间慢。这项研究通过计算机视觉和机器学习方法为未来的火灾报警检测系统提供了潜力和新趋势,包括选择输入特征以使用适当的方法和火灾报警探测系统的流程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancements in Fire Alarm Detection using Computer Vision and Machine Learning: A Literature Review
Fire is one of the most common and increasing emergencies that threaten public safety and social development. This can cause significant loss of life and damage. Fire detection systems play an important role in the early detection of fires. The purpose of this study is to provide a brief survey of the latest literature in the field, which can provide a foundation for researchers to develop a Fire Alarm Detection System with a Computer Vision and Machine Learning approach. The Computer Vision and Machine Learning approaches are popular and have been extensively studied because the advantages. The main challenges in fire detection systems are high false alarm rates and slow response times. This research presents potentials and emerging trends through Computer Vision and Machine Learning approaches for Fire Alarm Detection Systems in the future, including the selection of input features to the use of appropriate methods and the process flow of Fire Alarm Detection Systems.
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