Spatial Generalization
Spatial Generalization is a location privacy-preserving technique that belongs to the class of spatial obfuscation methods, distinguished by its systematic reduction of geographic precision through the aggregation of specific locations into broader, less precise regions to minimize re-identification risks while maintaining data utility.
77
Publications
4.1K
Citations
227
Authors
129
Institutions
Publications per year
2017–2026
15
77
Numerical Coordinate Regression with Convolutional Neural Networks
Aiden Nibali, Zhen He, Stuart Morgan et al. · arXiv (Cornell University) · 2018 · 188 citations · Full text
1–5 of 77
227
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Fraunhofer Institute for Intelligent Analysis and Information Systems, Germany
3 publications · 606 citations
3
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3
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3
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1–5 of 227
129
Fraunhofer Institute for Intelligent Analysis and Information Systems
Sankt Augustin, Germany
3 h-index
7 publications
1.4K citations

University of Edinburgh
Edinburgh, United Kingdom
3 h-index
3 publications
127 citations

Delft University of Technology
Delft, The Netherlands
3 h-index
3 publications
134 citations

Macquarie University
Sydney, Australia
3 h-index
3 publications
115 citations
National Institute of Mental Health
Bethesda, United States
2 h-index
6 publications
218 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
2 h-index
3 publications
153 citations

University of Alberta
Edmonton, Canada
2 h-index
2 publications
59 citations

IT University of Copenhagen
Copenhagen, Denmark
2 h-index
2 publications
102 citations
1–8 of 129
3 publications · 94 citations
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3 publications · 124 citations
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3 publications · 477 citations
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2 publications · 72 citations
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2 publications · 103 citations
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