通过无源射频数据的深度学习进行人的存在检测

Jenny Liu, A. Vakil, R. Ewing, Xiaoping Shen, Jia Li
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引用次数: 6

摘要

在自然灾害和监测系统等某些情况下,人类存在检测是一个关键领域。本文提出了一种利用软件无线电被动采集射频数据并应用深度学习神经网络检测人类存在的新方法。它提供了一个低成本和环保的解决方案。本研究的长期目标是开发一个基于深度学习的频谱监测系统。
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Human Presence Detection via Deep Learning of Passive Radio Frequency Data
Human presence detection is a critical field in certain circumstances such as natural disasters and surveillance systems. This paper presents a new approach that utilizes software defined radio to passively collect radio frequency data and applying deep learning neural network to detect human presence. It provides a low cost and environment friendly solution. The long term goal of this study is to develop a deep learning based spectrum monitoring system.
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