For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Multi-Channels LSTM Networks for Fence Activity Classification
Kelu HU Chunlei ZHENG Wei HE Xinghe BAO Yingguan WANG
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2018/08/01
Online ISSN: 1745-1361
Type of Manuscript: LETTER
Category: Biocybernetics, Neurocomputing
LSTM, neural network, fence, inertial sensors,
Full Text: PDF>>
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.