Abstract: Industrial few-shot anomaly detection (FSAD) requires identifying various abnormal states by leveraging as few normal samples as possible (abnormal samples are unavailable during training).

AI tools are frequently used in data visualization — this article describes how they can make data preparation more efficient ...

Professional, modular analysis of historical stock prices using multiple anomaly detection methods (Z-Score, Isolation Forest, DBSCAN, Prophet, Rolling Quantile). Includes multi-ticker comparison, ...

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...

A complete end-to-end Streaming Data Analytics (SDA) project that generates real-time weather data, applies SDA filters (Moving Average, EWMA), detects anomalies using Isolation Forest, and visualizes ...

Abstract: Anomaly detection is a key technology in quality control for automated production lines. Currently, 2D-based anomaly detection methods fail to identify geometric structure anomalies in ...

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...

Greysun is the Lead Guides Editor at GameRant, where he oversees game help coverage for everything from the biggest AAA releases to standout indie and live-service titles. Professionally, Greysun has ...