Anomaly Detection Visualization
Anomaly Detection Visualization is a visual analytics method that enables the identification and interpretation of rare or unexpected patterns in clinical and scientific data by integrating computational anomaly detection techniques with interactive visualization to support expert judgment and decision-making.
44
Publications
2K
Citations
155
Authors
57
Institutions
Publications per year
2017–2026
13
44
Sean Kandel, Ravi Parikh, Andreas Paepcke et al. · 2012 · 222 citations
Anomaly detection for visual analytics of power consumption data
Halldór Janetzko, Florian Stoffel, Sebastian Mittelstädt et al. · Computers & Graphics · 2013 · 109 citations · Full text
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Hong Kong University of Science and Technology, Hong Kong SAR China
2 publications · 72 citations
2
h-index
1–5 of 155
57

University of Skövde
Skövde, Sweden
4 h-index
8 publications
198 citations
Iowa State University
Ames, United States
3 h-index
5 publications
172 citations
University of California, Davis
Davis, United States
2 h-index
4 publications
72 citations
University of Konstanz
Konstanz, Germany
2 h-index
7 publications
496 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
2 h-index
4 publications
144 citations
Microsoft Research Asia (China)
Beijing, China
2 h-index
6 publications
216 citations
University of Pittsburgh
Pittsburgh, United States
2 h-index
2 publications
222 citations

Universidad de Granada
Granada, Spain
1 h-index
3 publications
48 citations
1–8 of 57
TVCG · 3 publications · 399 citations
3
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TIIS · 2 publications · 32 citations
2
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2 publications · 137 citations
2
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Repository · 2 publications · 50 citations
2
h-index
Conference · 1 publications · 75 citations
1
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