Worms is becoming a hotspot for predictive high-end algorithm development: The deep-tech company mAInthink.ai presents ...

AI-based anomaly detection helps engineers identify potential problems early, to improve process efficiency, says Rachel ...

To address this, researchers have developed multiclass anomaly detection algorithms that combine NSA with clonal selection algorithms (CSA) to improve classification accuracy and reduce runtime in ...

Renmin University researchers present a comprehensive survey of sampling- and sketch-based algorithms for distinct value estimation in big data, ...

Scienaptic AI, a leading provider of AI-powered credit decisioning, announced today that CommunityWide Federal Credit Union has selected its platform to enhance real-time fraud and anomaly detection ...

Although predicated on advanced math concepts, anomaly detection, or as the NIST Cybersecurity Framework 2.0 calls it, “adverse event analysis,” has over the past two decades been incorporated ...

In this paper, a content-based video anomaly detection algorithm (COVAD) is proposed, and its network structure is modified based on the original memory-based video anomaly detection algorithm.

Beyond individual models, Ghori has impacted the organizational structure as well. His work on anomaly detection accuracy has increased precision by 25%, directly enhancing financial risk mitigation.

Artificial Immune Systems (AIS) and anomaly detection algorithms are computational methods inspired by the adaptive and self-regulating properties of the biological immune system.