A new decision fusion technique for image classification

Mete Ozay, Fatos Tunay Yarman Vural

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

9 Citations (Scopus)

Abstract

In this study, we introduce a new image classification technique using decision fusion. The proposed technique, called Meta-Fuzzified Yield Value (Meta-FYV), is based on two-layer Stacked Generalization (SG) architecture [1]. At the base-layer, the system, receives a set of feature vectors of various dimensions and dynamical ranges and outputs hypotheses through fuzzy transformations. Then, the hypotheses created by the base layer transformations are concatenated for building a regression equation at meta-layer. Experimental evidence indicates that the Meta-FYV is superior compared to one of the most successful Fuzzy SG methods, introduced by Akbas [2].

Original languageEnglish
Title of host publication2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
PublisherIEEE Computer Society
Pages2189-2192
Number of pages4
ISBN (Print)9781424456543
DOIs
Publication statusPublished - 2009 Jan 1
Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
Duration: 2009 Nov 72009 Nov 10

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2009 IEEE International Conference on Image Processing, ICIP 2009
CountryEgypt
CityCairo
Period09/11/709/11/10

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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