GitHub

Bearing Fault Early Detection with Custom DSP Features

PhaseMag-AE — Our specialized autoencoder for joint magnitude/phase superframes Input: 256×256×2 (magnitude + phase channels from the custom transform superframes) Fully convolutional encoder–decoder ...
IEEE

Lightweight Real-Time Anomaly Detection and Prediction for Surveillance Videos Using a Self-Supervised Hybrid Autoencoder and Dynamic Graph CNN-LSTM Framework

Abstract: Anomaly detection in surveillance videos is a critical task for ensuring public safety, requiring both high accuracy and real-time efficiency. This study presents a novel lightweight anomaly ...
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 ...