Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...

This project implements a deep learning approach for anomaly detection in time-series data using a PyTorch-based Autoencoder. The model is trained to reconstruct normal data patterns and then used to ...

This project provides an unsupervised learning solution for detecting anomalies in time-series data, specifically demonstrated on synthetic network traffic. It leverages a Long Short-Term Memory (LSTM ...

Abstract: Multifunction radars are highly adaptive systems that employ phased array antennas and can simultaneously perform multiple working modes, such as search, tracking, recognition, and guidance.

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 ...