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 ...
Nature

Efficient anomaly detection in tabular cybersecurity data using large language models

In cybersecurity, anomaly detection in tabular data is essential for ensuring information security. While traditional machine learning and deep learning methods have shown some success, they continue ...

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 ...
Nature

Unsupervised anomaly detection for gearboxes based on the deep convolutional support generative adversarial network

The gearbox, as a key transmission device in the industrial field, may lead to severe vibrations or even failures when abnormalities occur. Therefore, with the increasing complexity of industrial ...
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 ...