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Enhancing Visual Concept Detection by a Novel Matrix Modular Scheme on SVM

  • Zhong-Qiu Zhao
  • Hervé Glotin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5706)

Abstract

A novel Matrix Modular Support Vector Machine(MMSVM) classifier is proposed to partition a visual concept problem into many easier two-class problems.This MMSVM shows significant detection improvements on the ImageClef2008 VCDT task, with a relative reduction of 15% of the classification error, compared with usual SVMs.

Keywords

Visual Concept Matrix Modular Modular Neural Network Palmprint Recognition Vote Machine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Zhong-Qiu Zhao
    • 1
    • 2
  • Hervé Glotin
    • 1
  1. 1.Systems and Information Sciences Lab. (LSIS)UMR CNRS &, Univ. Sud Toulon-VarFrance
  2. 2.Computer and Information SchoolHefei Univ. of TechnologyChina

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