New Study on Synthetic Data-Driven Sub-surface Anomaly Detection by VE3 AI Research

VE3 AI Research publishes a study on synthetic data, magnetic dipole modeling, and unsupervised AI for scalable anomaly ...

AI-based tissue anomaly detection may reduce duration of liver cancer surgery

A liver cancer diagnosis frequently leads to surgery, with the goal of completely removing all malignant tissue. To ensure ...
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 ...
dbta

Acceldata’s Adaptive AI Anomaly Detection Supercharges Data Quality

Acceldata, a leading provider of data observability and agentic data management solutions, is announcing a new capability designed to amplify the power of agentic reasoning within the company’s xLake ...
Electronic Design

Using AI Anomaly Detection in Embedded Applications

Machine-learning models are very good at anomaly detection when properly trained. These artificial-intelligence systems are currently used to identify people, places, and things for self-driving cars ...
Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...