Point Outlier Detection
Point Outlier Detection is a type of outlier detection method that identifies individual data instances significantly deviating from the majority of the dataset based on their intrinsic properties, without reference to temporal or contextual dependencies.
461
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40K
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1.9K
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702
Institutions
Publications per year
2017–2026
170
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461
IsoplotR: A free and open toolbox for geochronology
Pieter Vermeesch · Geoscience Frontiers · 2018 · 3.4K citations · Full text
Universal outlier detection for PIV data
Jerry Westerweel, Fulvio Scarano · Experiments in Fluids · 2005 · 1.2K citations
Efficient algorithms for mining outliers from large data sets
Sridhar Ramaswamy, Rajeev Rastogi, Kyuseok Shim · 2000 · 1.1K citations · Full text
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Carnegie Mellon University
Pittsburgh, United States
11 h-index
28 publications
6.1K citations

Chinese Academy of Sciences
Beijing, China
8 h-index
20 publications
807 citations
University of Tsukuba
Tsukuba, Japan
7 h-index
11 publications
1.1K citations
Google (United States)
Mountain View, United States
6 h-index
7 publications
1.2K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
6 h-index
9 publications
208 citations
ETH Zurich
Zurich, Switzerland
6 h-index
14 publications
346 citations
Tongji University
Shanghai, China
6 h-index
12 publications
722 citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
5 h-index
8 publications
3.2K citations
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TKDE · 12 publications · 2.1K citations
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TPAMI · 9 publications · 783 citations
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Repository · 7 publications · 759 citations
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6 publications · 2.6K citations
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6 publications · 165 citations
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