Analyzing real life cases, it’s easy to notice that the issue of detecting anomalies is usually met in the context of various fields of application, including but not limited to intrusion detection, ...

What is explainable AI (XAI)? What are some of the use cases for XAI? What are the technology requirements for implementing XAI? Anomaly detection is the process of identifying when something deviates ...

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 ...

Anomaly detection is the process of identifying events or patterns that differ from expected behavior. Anomaly detection can range from simple outlier detection to complex machine learning algorithms ...

PORTLAND, Ore., Oct. 9, 2019 /PRNewswire/ -- SensiML™ Corporation, a leading developer of AI tools for building intelligent IoT endpoints, today announced that its SensiML Analytics Toolkit delivers ...

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 ...

A good way to see where this article is headed is to take a look at the screenshot in Figure 1 and the graph in Figure 2. The demo program begins by loading a tiny 10-item dataset into memory. The ...

The US Army Analytics Group (AAG) provides analytical services for various organizational operations and functions, including cybersecurity. AAG signed a Cooperative Research and Development Agreement ...

In industry, the detection of anomalies such as scratches, dents, and discolorations is crucial to ensure product quality and safety. However, conventional methods rely on heavy computational ...

TNO’s advanced detection, threat management, and orchestration expertise ensures that critical IT and OT have sufficient ...