A knowledge-based ("expert") classifier was designed for classifying ship silhouettes generated from forward-looking infrared (FLIR) imagery. A knowledge-base is constructed based on interviews with a U.S. Navy officer along with confirming evidence from Jayne's Fighting Ships. This knowledge provides the means to set-up a ruled-based sequential decision tree or net. The conditions of the production rules deal with silhouette "humps" and their properties such as the number, spacing, relative placement on deck line, and the like. This classifier was applied to a sample consisting of about 500 sample silhouettes distributed about uniformly over eight classes of ship targets. Results were equal or better than results using a more "conventional" classifier.


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    Titel :

    A Knowledge-Based Approach To Ship Identification


    Beteiligte:
    McLaren, R. W. (Autor:in) / Lin, H .-Y . (Autor:in)

    Kongress:

    Applications of Artificial Intelligence III ; 1986 ; Orlando,United States


    Erschienen in:

    Erscheinungsdatum :

    26.03.1986





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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