Visual Studio Magazine

Data Anomaly Detection Using a Neural Autoencoder with C#

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 ...
BIOENGINEER

Unsupervised autoencoder with IQR threshold detects 5G DoS/DDoS traffic in benchmark study

NIDD, a deep autoencoder trained only on benign flows and thresholded with an adaptive IQR rule detected 321,012 of 321,357 ...
BIOENGINEER

AI Architecture Joins Load Forecasting, Anomaly Detection, and Predictive Energy Management

Controlled anomaly injection has the advantage of producing reproducible ground-truth labels, which is rare in real metering ...
Nature

Autoencoder Techniques in Anomaly Detection and Feature Learning

Autoencoders are a class of unsupervised neural networks designed to learn efficient data representations by encoding inputs into a compact latent space and then reconstructing them. Their versatility ...