preprintarXiv (Cornell University)Jan 10, 2019GREEN OA

Deep Learning for Anomaly Detection: A Survey

University of Sydney · RoZetta Institute

Indexed inarxivdatacite

Abstract

Anomaly detection is an important problem that has been well-studied within diverse research areas and application domains. The aim of this survey is two-fold, firstly we present a structured and comprehensive overview of research methods in deep learning-based anomaly detection. Furthermore, we review the adoption of these methods for anomaly across various application domains and assess their effectiveness. We have grouped state-of-the-art research techniques into different categories based on the underlying assumptions and approach adopted. Within each category we outline the basic anomaly detection technique, along with its variants and present key assumptions, to differentiate between normal and anomalous…

Citation impact

1,207
total citations
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References
419
Citations per year

Authors

2

Topics & keywords

Keywords
  • Anomaly detection
  • Anomaly (physics)
  • Deep learning
  • Artificial intelligence
  • Computer science
  • Physics
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