Feature extraction for subtle anomaly detection using semi-supervised learning

Yeni Li; Hany S. Abdel‐Khalik; Ahmad Al Rashdan; Jacob Farber

doi:10.1016/j.anucene.2022.109503

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Feature extraction for subtle anomaly detection using semi-supervised learning

Yeni Li Hany S. Abdel‐Khalik Ahmad Al Rashdan Jacob Farber

Year: 2022 Journal: Annals of Nuclear Energy Vol: 181 Pages: 109503-109503 Publisher: Elsevier BV

DOI: 10.1016/j.anucene.2022.109503

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Keywords:

Anomaly detection Pattern recognition (psychology) Artificial intelligence Anomaly (physics) Computer science Feature (linguistics) Feature extraction Extraction (chemistry) Supervised learning Chromatography Artificial neural network Physics

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Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Fault Detection and Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

Machine Fault Diagnosis Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Feature extraction for subtle anomaly detection using semi-supervised learning

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