Publikation: Towards Automatic Feature Vector Optimization for Multimedia Applications
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2008
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Proceedings of the 2008 ACM symposium on Applied computing - SAC '08. New York, New York, USA: ACM Press, 2008, pp. 1197-1201. ISBN 978-1-59593-753-7. Available under: doi: 10.1145/1363686.1363964
Zusammenfassung
We systematically evaluate a recently proposed method for unsupervised discrimination power analysis for feature selection and optimization in multimedia applications. A series of experiments using real and synthetic benchmark data is conducted, the results of which indicate the suitability of the method for unsupervised feature selection and optimization. We present an approach for generating synthetic feature spaces of varying discrimination power, modeling main characteristics from real world feature vector extractors. A simple, yet powerful visualization is used to communicate the results of the automatic analysis to the user.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Feature vectors, discrimination power, feature selection, Self-organizing map
Konferenz
The 4th ACM symposium on Software visuallization - SoftVis '08, 16. März 2008 - 20. März 2008, Fortaleza, Ceara, Brazil
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SCHRECK, Tobias, Dieter W. FELLNER, Daniel A. KEIM, 2008. Towards Automatic Feature Vector Optimization for Multimedia Applications. The 4th ACM symposium on Software visuallization - SoftVis '08. Fortaleza, Ceara, Brazil, 16. März 2008 - 20. März 2008. In: Proceedings of the 2008 ACM symposium on Applied computing - SAC '08. New York, New York, USA: ACM Press, 2008, pp. 1197-1201. ISBN 978-1-59593-753-7. Available under: doi: 10.1145/1363686.1363964BibTex
@inproceedings{Schreck2008Towar-5625,
year={2008},
doi={10.1145/1363686.1363964},
title={Towards Automatic Feature Vector Optimization for Multimedia Applications},
isbn={978-1-59593-753-7},
publisher={ACM Press},
address={New York, New York, USA},
booktitle={Proceedings of the 2008 ACM symposium on Applied computing - SAC '08},
pages={1197--1201},
author={Schreck, Tobias and Fellner, Dieter W. and Keim, Daniel A.}
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