Topological Compression
Topological Compression is a data reduction technique that preserves essential topological features of a scalar field or dataset by encoding its critical structures—such as connected components, saddles, and peaks—using a simplified topological representation, thereby enabling efficient storage and visualization while maintaining fidelity to the underlying topology.
39
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2.9K
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93
Authors
47
Institutions
Publications per year
2017–2026
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Image compression by self-organized Kohonen map
Christophe Amerijckx, Michel Verleysen, Philippe Thissen et al. · IEEE Transactions on Neural Networks · 1998 · 127 citations
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University of North Carolina at Chapel Hill, United States
2 publications · 58 citations
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2
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47
Georgia Institute of Technology
Atlanta, United States
2 h-index
2 publications
1.3K citations
Jeonbuk National University
Jeonju, South Korea
2 h-index
2 publications
50 citations
Max Planck Institute for Informatics
Saarbrücken, Germany
2 h-index
6 publications
171 citations
Toshiba (Japan)
Tokyo, Japan
2 h-index
18 publications
1.1K citations
The University of Texas at Austin
Austin, United States
2 h-index
6 publications
375 citations
University of California, Santa Cruz
Santa Cruz, United States
2 h-index
6 publications
216 citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
1 h-index
2 publications
196 citations
Teradyne (United States)
Boston, United States
1 h-index
1 publications
30 citations
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3 publications · 106 citations
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TVCG · 2 publications · 738 citations
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Conference · 1 publications · 44 citations
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1 publications · 39 citations
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Repository · 1 publications · 118 citations
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