Scientific Research Publishing

Covariant-Scale: Riemannian Manifold Learning for Scale-Invariant Video Anomaly Detection ()

Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera images ...
IEEE

Enhancing Software Reliability through Anomaly Detection: Implementing Variational Autoencoders for Real-time Performance Monitoring and Error Prediction

Abstract: To secure performance with minimal system downtimes, the reliability of any software is the primary focus. This paper proposes a combined strategy of using deep learning techniques in an ...
C&EN

Mapping Conformational and Kinetic Landscapes of 14-3-3σ/α-Synuclein Assembly via Variational Autoencoders and Markov State Models

The interaction between the molecular chaperone 14-3-3σ and the intrinsically disordered protein α-synuclein is implicated in the pathogenesis of Parkinson’s disease, yet its dynamic mechanism remains ...
IEEE

Detection of Unknown Attacks Through Encrypted Traffic: A Gaussian Prototype-Aided Variational Autoencoder Framework

Abstract: The identification of encrypted network traffic presents a pivotal challenge in detecting unknown malicious traffic. Unlike closed-set identification, which primarily classifies known ...