Spectral Unmixing is an important technique in remote sensing for analyzing hyperspectral images to identify endmembers and estimate fractional abundance maps. Over the past few decades, significant ...

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 ...

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 ...