Cyber Defense Magazine

Encrypted Telemetry for AI – Driven Detection

As organizations continue to move their systems to the cloud, they face a tough question: How do you keep an eye on ...
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
IEEE

Sample Similarity-Guided Spatial-Spectral Masked Autoencoder for Hyperspectral Anomaly Detection

Hyperspectral anomaly detection aims to identify targets that are significantly different from the surrounding background within hyperspectral image (HSI). The lack of prior information poses a ...
IEEE

Convolutional Autoencoder-Based Anomaly Detection in PPG Signals Using a Necklace Wearable Device

Abstract: Detecting anomalies in PPG signals is crucial for the early identification of cardiovascular conditions, such as arrhythmias, poor perfusion, or stress induced by daily activities, thereby ...
GitHub

Variational autoencoder with Kolmogorov-Arnold Network for spatial domain detection.

Experiments were executed on NVIDIA A40 of 46068MiB memory in linux with torch==2.1.0+cu121, torch_geometric==2.3.1, torch-sparse==0.6.18+pt21cu121, and torchvision==0.16.0+cu121. The stkan is an ...
Scientific Research Publishing

An, J. and Cho, S. (2015) Variational Autoencoder Based Anomaly Detection Using Reconstruction Probability. Special Lecture on IE, 2, 1-18.

ABSTRACT: 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 ...