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, ...

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 ...

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 ...

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 ...

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 ...

Identifying anomalies in the operations of computer systems that control critical safety and security functions calls for extensive expertise, and the actions required need to be tested, analysed and ...

SolarWinds, a provider of IT management software, is introducing machine learning-enabled database anomaly detection and an automated management API in the latest version of Database Performance ...

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 ...

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 ...