Visual Studio Magazine

Anomaly Detection Using Principal Component Analysis (PCA)

A good way to see where this article is headed is to take a look at the screen shot of a demo program shown in Figure 1. The demo sets up a dummy dataset of six items: [ 5.1 3.5 1.4 0.2] [ 5.4 3.9 1.7 ...
JSTOR Daily

Anomaly Detection for Insulated Gate Bipolar Transistor (IGBT) under Power Cycling using Principal Component Analysis and K-Nearest Neighbor Algorithm

Insulated Gate Bipolar Transistor (IGBT) is a power electronic transistor used in medium to high power applications such as hybrid cars, railway traction motors, switch mode power supplies, and wind ...
TechCrunch

Financial firms should leverage machine learning to make anomaly detection easier

Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions. Broadly speaking, a true anomaly is one that deviates from the ...
EurekAlert!

COVAD: Content-oriented video anomaly detection using a self attention-based deep learning model

Video anomaly detection is a research hotspot in the field of computer vision, attracting many researchers.Video anomaly detection differs from traditional video analysis. Usually, abnormal events ...