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A review of novelty detection
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“This phenomenon introduces various uncertainties into the system's outcomes [4,5].”
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Metadata
- Authors
- Pimentel, M. A. F., Clifton, D. A., Clifton, L., & Tarassenko, L.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Pimentel, Marco A.F.
- Venue
- Signal Processing
- Publisher
- Elsevier BV
- Published
- 2014-06
- Volume
- 99
- Pages
- 215-249
- ISSN
- 0165-1684 (ISSN-L)
- OpenAlex
- W2115627867
- Cited by
- 1,649
- References
- 322
- Citations by year
- 2026: 94 · 2025: 114 · 2024: 137 · 2023: 140 · 2022: 161 · 2021: 199 · 2020: 219 · 2019: 170 · 2018: 162 · 2017: 103 · 2016: 81 · 2015: 49 · 2014: 17
- FWCI
- 77.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Signal Processing (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Adversarial Robustness in Machine Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Immune Systems Applications
- Keywords
- novelty detection, one-class classification, anomaly detection, critical systems
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