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      Fusion de classifieurs pour la classification d'images sonar

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          Abstract

          In this paper, we present some high level information fusion approaches for numeric and symbolic data. We study the interest of such method particularly for classifier fusion. A comparative study is made in a context of sea bed characterization from sonar images. The classi- fication of kind of sediment is a difficult problem because of the data complexity. We compare high level information fusion and give the obtained performance. nullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnullnull

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          Fuzzy sets as a basis for a theory of possibility

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            Methods of combining multiple classifiers and their applications to handwriting recognition

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              The combination of evidence in the transferable belief model

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                Author and article information

                Journal
                12 June 2008
                2012-01-06
                Article
                0806.2006
                f680f5b9-b380-4f07-a04b-d9bd5425b273

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                Revue Nationale des Technologies de l'Information E, 5 (2005) 259-268
                cs.CV cs.AI
                ccsd

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