EurekAlert!

Chung-Ang University researchers review deep learning-based methods to detect time series data anomaly

Researchers analyze state-of-the-art approaches, limitations, and applications of deep learning-based anomaly detection in multivariate time series Monitoring financial security, industrial safety, ...
InfoWorld

How to model time-series anomaly detection for IoT

Machines fail. By creating a time-series prediction model from historical sensor data, you can know when that failure is coming Anomaly detection covers a large number of data analytics use cases.
JSTOR Daily

A Comparison of Multivariate Outlier Detection Methods For Finding Hyperspectral Anomalies

Timothy E. Smetek, Kenneth W. Bauer Jr. Hyperspectral anomaly detection is a useful means for using hyperspectral imagery to locate unusual objects. Current anomaly detection methods commonly use ...
insideHPC

Detecting Anomalies in Time Series Data: Deciphering the Noise and Zoning in on the Signals

You have the data. How do you make sense of it? The Internet of Things (IoT) is no longer a fancy marketing term thrown in to close a critical deal – it’s all around us. In the digital age, everyone ...
Business Wire

Falkonry Unveils GPU-Based, High-Speed Time Series Anomaly Detection Application

CUPERTINO, Calif.--(BUSINESS WIRE)--Falkonry today announced an automated anomaly detection application called Falkonry Insight which operates on high-speed sensor time series data. Insight is the ...
InfoWorld

Oracle adds machine learning features to MySQL HeatWave

Oracle is adding new machine learning features to its data analytics cloud service MySQL HeatWave. MySQL HeatWave combines OLAP (online analytical processing), OLTP (online transaction processing), ...