Multi-Channels LSTM Networks for Fence Activity Classification

Kelu HU  Chunlei ZHENG  Wei HE  Xinghe BAO  Yingguan WANG  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.8   pp.2173-2177
Publication Date: 2018/08/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDL8004
Type of Manuscript: LETTER
Category: Biocybernetics, Neurocomputing
Keyword: 
LSTM,  neural network,  fence,  inertial sensors,  

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Summary: 
We propose a novel neural networks model based on LSTM which is used to solve the task of classifying inertial sensor data attached to a fence with the goal of detecting security relevant incidents. To evaluate it we deployed an experimental fence surveillance system. By comparing experimental data of different approaches we find out that the neural network outperforms the baseline approach.