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  On the (Un)Suitability of Strict Feature Definitions for Uncertain Data

Weinkauf, T. (2014). On the (Un)Suitability of Strict Feature Definitions for Uncertain Data. In C. D. Hansen, M. Chen, C. R. Johnson, A. E. Kaufman, & H. Hagen (Eds.), Scientific Visualization (pp. 45-50). London: Springer. doi:10.1007/978-1-4471-6497-5_4.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0024-5315-F Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0024-B709-4
Genre: Book Chapter

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 Creators:
Weinkauf, Tino1, Author           
Affiliations:
1Computer Graphics, MPI for Informatics, Max Planck Society, ou_40047              

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 Abstract: We discuss strategies to successfully work with strict feature definitions such as topology in the presence of noisy/uncertain data. To that end, we review previous work from the literature and identify three strategies: the development of fuzzy analogs to strict feature definitions, the aggregation of features, and the filtering of features. Regarding the latter, we will present a detailed discussion of filtering ridges/valleys and topological structures.

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Language(s): eng - English
 Dates: 20142014
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: weinkauf14b
DOI: 10.1007/978-1-4471-6497-5_4
 Degree: -

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Title: Scientific Visualization
  Subtitle : Uncertainty, Multifield, Biomedical, and Scalable Visualization
Source Genre: Book
 Creator(s):
Hansen, Charles D., Editor
Chen, Min, Editor
Johnson, Christopher R., Editor
Kaufman, Arie E., Editor
Hagen, Hans, Editor
Affiliations:
-
Publ. Info: London : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 45 - 50 Identifier: ISBN: 978-1-4471-6496-8