Randomized Geometric Data Structures
Randomized Geometric Data Structures is a systematic framework for organizing spatial data that incorporates randomness in its construction or query procedures to achieve efficient expected performance and robustness in geometric computations.
11
Publications
526
Citations
15
Authors
10
Institutions
Publications per year
2017–2026
1
11
Space-filling curves and their use in the design of geometric data structures
Tetsuo Asano, Desh Ranjan, Thomas Roos et al. · Theoretical Computer Science · 1997 · 222 citations
Statistical Analysis of Geometric Computation
Kenichi Kanatani · CVGIP Image Understanding · 1994 · 30 citations
1–5 of 11
15
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2
h-index
2
h-index
1
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1
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1–5 of 15
10
Duke University
Durham, United States
2 h-index
4 publications
140 citations

New Mexico State University
Las Cruces, United States
1 h-index
1 publications
222 citations

Osaka Electro-Communication University
Neyagawa, Japan
1 h-index
1 publications
222 citations

Kiryu University
Midori, Japan
1 h-index
1 publications
30 citations
Freie Universität Berlin
Berlin, Germany
1 h-index
1 publications
222 citations
University of Chicago
Chicago, United States
1 h-index
1 publications
27 citations
University of Miami
Coral Gables, United States
1 h-index
1 publications
10 citations
Max Planck Institute for Informatics
Saarbrücken, Germany
1 h-index
5 publications
175 citations
1–8 of 10
Repository · 1 publications · 35 citations
1
h-index
1 publications · 10 citations
1
h-index
1 publications · 27 citations
1
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Conference · 1 publications · 21 citations
1
h-index
Conference · 1 publications · 12 citations
1
h-index
1–5