This project implements a system for detecting anomalies in time series data collected from Prometheus. It uses an LSTM (Long Short-Term Memory) autoencoder model built with TensorFlow/Keras to learn ...

This project implements an LSTM Autoencoder to detect anomalies in EKG (electrocardiogram) data. The goal is to identify irregular heartbeats (arrhythmias) by training an unsupervised model on normal ...

Tensor representation (TR) can sensitively perceive the inherent prior structure of hyperspectral images, showing broad prospects in hyperspectral anomaly detection (HAD). However, current models are ...

Industrial process data are usually affected by random and gross errors leading to deviation from the true value and violation of process constraints. Traditional data reconciliation methods rely on ...