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Authors: Sayan Hazra & Sankalpa Chowdhury LSTM autoencoder based anomaly detection using Keras and Tensorflow backend. Here in this project we have done a comparative study between Simple LSTM Network ...
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Autoencoder (AE) base architecture has been chosen to leverage its dimension reduction capabilities for relevant feature extraction. Our proposed scheme results show a considerable improvement from ...
To address the issue, this study proposed an innovative anomaly detection algorithm, namely the LSTM Autoencoder with Gaussian Mixture Model (LAGMM). Although these new technologies have many ...