Topological Methods in Data Analysis and Visualization III Theory, Algorithms, and Applications /

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 simplif...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Bremer, Peer-Timo (Editor), Hotz, Ingrid (Editor), Pascucci, Valerio (Editor), Peikert, Ronald (Editor)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2014.
Series:Mathematics and Visualization,
Subjects:
Online Access:Full Text via HEAL-Link
Description
Summary: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.
Physical Description:X, 279 p. 98 illus., 69 illus. in color. online resource.
ISBN:9783319040998
ISSN:1612-3786