A random network ensemble for recognition

Kwontaeg Choi, Kar Ann Toh, Hyeran Byun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


In this paper, we propose a random network ensemble for face recognition problem, particularly for images with a large appearance variation and with a limited number of training set. In order to reduce the correlation within the network ensemble using a single type of feature extractor and classifier, localized random facial features have been constructed together with internally randomized networks. The ensemble classifier is finally constructed by combining these multiple networks via a sum rule. The proposed method is shown to have a better accuracy(31.5% and 15.3% improvements on AR and EYALEB databases respectively) and a better efficiency than that of the widely used PCA- SVM.

Original languageEnglish
Title of host publicationAdvances in Biometrics - Third International Conference, ICB 2009, Proceedings
Number of pages10
Publication statusPublished - 2009
Event3rd International Conference on Advances in Biometrics, ICB 2009 - Alghero, Italy
Duration: 2009 Jun 22009 Jun 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5558 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other3rd International Conference on Advances in Biometrics, ICB 2009

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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