Deep Learning and XAI Techniques for Anomaly Detection

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Understanding Deep Learning Anomaly Detection

Anomaly detection is an active research field widely applied to many commercial and mission-critical applications, including healthcare, fraud detection, industrial predictive maintenance, and cybersecurity. It is a process of discovering outliers, abnormal patterns, and unusual observations that deviate from established normal behaviors and expected characteristics in a system, dataset, or environment.

Many anomaly detection applications require domain-specific knowledge to extract actionable insights in a timely manner for informed decision-making and risk mitigation. For example, early detection of equipment performance degradation prevents unplanned downtime, whereas early discovery of disease ...