Cascaded SVMs in Pattern Classification for Time-Sensitive Separating

Author

Wang Ruihu ; Fang Bin ; Hu Zhangping ; Chen Liang ; Wang Weihua

Author_Institution

Coll. of Comput. Sci., Chongqing Univ., Chongqing, China

fYear

2010

fDate

2-4 April 2010

Firstpage

640

Lastpage

644

Abstract

This paper introduced some fundamental background knowledge of Support Vector Machine, including VC dimension, separable hyperplane, and feature space as well. Two kinds of cascaded SVMs architecture are reviewed, i.e. parallel and serial structure Parallel SVMs can reduce the run time effectively. And serial SVMs is being used for multi-class separating, and discard the negative samples at the early stage. In the end we proposed two potential applications using cascaded SVMs.

Keywords

pattern classification; support vector machines; VC dimension; cascaded SVM; pattern classification; separable hyperplane; serial structure parallel SVM; support vector machine; time-sensitive separating; Application software; Computer architecture; Computer science; Face recognition; Machine intelligence; Pattern classification; Signal processing; Support vector machine classification; Support vector machines; Virtual colonoscopy; Support Vector Mahince; cascaded architecturet; classification; time-complexity;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology and Security Informatics (IITSI), 2010 Third International Symposium on

Conference_Location

Jinggangshan

Print_ISBN

978-1-4244-6730-3

Electronic_ISBN

978-1-4244-6743-3

Type

conf

DOI

10.1109/IITSI.2010.56

Filename

5453707