Opinion
SpaceNewsOpinion

We need a ‘Planetary Neural Network’ for AI-enabled space infrastructure protection

For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...
GitHub

aadvaitav/cube-sat-anomaly-detection

This project implements an Bidirectional LSTM Autoencoder-based anomaly detection system for CubeSat telemetry monitoring. It processes multi-channel satellite telemetry data in real-time, detects ...
IEEE

Fault Prognosis of Gearbox Based on Convolutional LSTM Autoencoder using Current Signal Data

Abstract: Fault prognosis and accurate prediction of gearbox remaining useful life (RUL) are challenging due to the lack of mathematical models and external factors like operating conditions and ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...
Scientific Research Publishing

Alrawais, A., Alhothaily, A., Hu, C. and Cheng, X. (2021) LSTM-Based Intrusion Detection for IoT Networks. IEEE Transactions on Network and Service Management, 18, 1712-1725.

ABSTRACT: The rapid proliferation of the Internet of Things (IoT) and Industrial IoT (IIoT) has revolutionized industries through enhanced connectivity and automation. However, this expansion has ...
IEEE

Video Anomaly Detection using Variational Convolutional LSTM Autoencoder

Abstract: Unintentional, inadvertent, unanticipated, or unplanned events are referred to as anomalies or abnormal events. Anomaly detection in surveiiance video has been a topic of active research for ...