Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions. Broadly speaking, a true anomaly is one that deviates from the ...

The proposed industrial anomaly detection model is computationally efficient, memory-friendly, and also suitable for low-light conditions, common in manufacturing environments, making it well-suited ...

Abstract: Fraud in supply chain operations poses significant risks to businesses, including financial losses, operational inefficiencies, and erosion of stakeholder trust. With the increasing ...

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 ...

Anomaly detection in the context of data science is detecting a data sample that is out of the ordinary and does not fit into the general data pattern (or an outlier). This deviation can result from a ...

Payments risk management has evolved significantly, shifting from simple rules-based systems to sophisticated machine learning (ML) models that enable businesses to better detect and mitigate fraud.

I am the VP of Engineering at Apriorit, a software development company that provides engineering services globally to tech companies. Social media is an indispensable tool for businesses to engage ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More At the advent of the modern AI era, when it was discovered that powerful ...

Video anomaly detection is a research hotspot in the field of computer vision, attracting many researchers.Video anomaly detection differs from traditional video analysis. Usually, abnormal events ...