Anomaly Score Normalization
Anomaly Score Normalization is a methodological procedure in anomaly detection that transforms raw anomaly scores into a standardized range to enable consistent comparison across different models or datasets by mitigating score scale heterogeneity.
10
Publications
495
Citations
35
Authors
15
Institutions
Publications per year
2017–2026
8
Parents
10
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows
Jiawei Yu, Ye Zheng, Xiang Wang et al. · arXiv (Cornell University) · 2021 · 215 citations · Full text
Enhanced anomaly scores for isolation forests
Antonella Mensi, Manuele Bicego · Pattern Recognition · 2021 · 53 citations
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15
Institut Mines-Télécom
Palaiseau, France
1 h-index
1 publications
10 citations
Institut Polytechnique de Paris
Palaiseau, France
1 h-index
1 publications
10 citations

University of Surrey
Guildford, United Kingdom
1 h-index
3 publications
138 citations
East China University of Science and Technology
Shanghai, China
1 h-index
6 publications
96 citations
Laboratoire d'Intégration des Systèmes et des Technologies
Palaiseau, France
1 h-index
3 publications
30 citations

University of Toyama
Toyama, Japan
1 h-index
1 publications
34 citations
UK Dementia Research Institute
London, United Kingdom
1 h-index
2 publications
92 citations
Télécom SudParis
Évry-Courcouronnes, France
1 h-index
1 publications
10 citations
1–8 of 15
Repository · 2 publications · 236 citations
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1 publications · 16 citations
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1 publications · 29 citations
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1 publications · 48 citations
1
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2 publications · 66 citations
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