Abstract: Hyperspectral unmixing is significant for advancing remote sensing (RS) applications, aiming at extracting the spectra of pure materials (called endmembers) and obtaining their proportions ...
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 ...
AutoencoderZ is an advanced Autoencoder model designed for dimensionality reduction of various data types, such as seismometer and strainmeter data. It features an encoder-decoder architecture that ...
Abstract: The growth of interconnected devices has led to an enormous volume of temporal data that requires specialized compression models for efficient storage. Besides this, most applications need ...