A distributed sensor object recognition scheme that uses object features collected by several sensors is presented. Recognition is performed by a binary decision tree generated from a training set. The scheme does not assume the availability of any probability density functions, thus it is practical for nonparametric object recognition. Simulations have been performed for Gaussian feature objects, and some of the results are presented.<>


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    Titel :

    Distributed sensor data fusion with binary decision trees


    Beteiligte:
    Demirbas, K. (Autor:in)


    Erscheinungsdatum :

    01.09.1989


    Format / Umfang :

    531342 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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