Editors:
- Covers the full range of cutting-edge research in the sector
- Features work by the most prominent and respected researchers
- Addresses key issues such as representing big data
- Contains papers on the latest developments including fast homology computation
- Includes supplementary material: sn.pub/extras
Part of the book series: Mathematics and Visualization (MATHVISUAL)
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Table of contents (17 papers)
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Front Matter
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Simplification, Approximation, and Distance Measures
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Front Matter
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Applications
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Front Matter
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About this book
This collection of peer-reviewed conference papers provides comprehensive coverage of cutting-edge research in topological approaches to data analysis and visualization. It encompasses the full range of new algorithms and insights, including fast homology computation, comparative analysis of simplification techniques, and key applications in materials and medical science. The volume also features material on core research challenges such as the representation of large and complex datasets and integrating numerical methods with robust combinatorial algorithms.
Reflecting the focus of the TopoInVis 2013 conference, the contributions evince the progress currently being made on finding experimental solutions to open problems in the sector. They provide an inclusive snapshot of state-of-the-art research that enables researchers to keep abreast of the latest developments and provides a foundation for future progress. With papers by some of the world’s leading experts in topological techniques, this volume is a major contribution to the literature in a field of growing importance with applications in disciplines that range from engineering to medicine.
Editors and Affiliations
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Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, USA
Peer-Timo Bremer
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Comparative Visualization Group, Konrad-Zuse-Zentrum für Informationstechnik, Berlin, Germany
Ingrid Hotz
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School of Computing and SCI Institute, University of Utah, Salt Lake City, USA
Valerio Pascucci
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Department of Computer Science, ETH Zürich, Zürich, Switzerland
Ronald Peikert
Bibliographic Information
Book Title: Topological Methods in Data Analysis and Visualization III
Book Subtitle: Theory, Algorithms, and Applications
Editors: Peer-Timo Bremer, Ingrid Hotz, Valerio Pascucci, Ronald Peikert
Series Title: Mathematics and Visualization
DOI: https://doi.org/10.1007/978-3-319-04099-8
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-04098-1Published: 07 May 2014
Softcover ISBN: 978-3-319-38165-7Published: 23 August 2016
eBook ISBN: 978-3-319-04099-8Published: 22 April 2014
Series ISSN: 1612-3786
Series E-ISSN: 2197-666X
Edition Number: 1
Number of Pages: X, 279
Number of Illustrations: 29 b/w illustrations, 69 illustrations in colour
Topics: Visualization, Analysis, Topology, Geometry, Image Processing and Computer Vision, Pattern Recognition