It uses an LSTM (Long Short-Term Memory) autoencoder model built with TensorFlow/Keras ... model training, and real-time anomaly detection, exposing results via a Prometheus exporter.

This project implements an LSTM Autoencoder to detect anomalies in EKG (electrocardiogram ... making them ideal for this type of sequence-based anomaly detection. These visuals illustrate the loss ...

However, the traditional anomaly detection methods often rely on static thresholds ... This study proposes a Long Short-Term Memory (LSTM) autoencoder-based approach to detect Man-in-the-Middle (MiTM) ...

To address these challenges, we propose a novel hybrid machine anomaly detection methodology that integrates an innovative pretext task-based self-supervised learning framework with vibration ...