Title: Classification techniques in pattern recognition
Authors: Zheng, Lihong
He, Xiangjian
Citation: WSCG '2005: Posters: The 13-th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2005 in co-operation with EUROGRAPHICS, University of West Bohemia, Plzen, Czech Republic, p. 77-78.
Issue Date: 2005
Publisher: Václav Skala - UNION Agency
Document type: konferenční příspěvek
URI: http://wscg.zcu.cz/WSCG2005/Papers_2005/Poster/!WSCG2005_Poster_Proceedings_Final.pdf
ISBN: 80-903100-8-7
Keywords: rozpoznávání vzorů;klasifikační techniky;analýza hlavních komponent
Keywords in different language: pattern recognition;classification techniques;principal component analysis
Abstract: In this paper, we review some pattern recognition schemes published in recent years. After giving the general processing steps of pattern recognition, we discuss several methods used for steps of pattern recognition such as Principal Component Analysis (PCA) in feature extraction, Support Vector Machines (SVM) in classification, and so forth. Different kinds of merits are presented and their applications on pattern precognition are given. The objective of this paper is to summarize and compare some of the methods for pattern recognition, and future research issues which need to be resolved and investigated further are given along with the new trends and ideas.
Rights: © Václav Skala - UNION Agency
Appears in Collections:WSCG '2005: Posters

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Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/920

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