Detecting an aircraft solely by its infrared (IR) signature in real time can be extremely challenging task depending on the image background clutter. Neural networks offer a reliable method of detecting targets (aircraft) against a multitude of background scenes and a variety of environmental conditions. Neural networks can rapidly "learn" to differentiate between background clutter and fast moving, small, "hot" (temperature) targets. A neural network real time video processor (NN-RTVP) presented in this paper was inspired by and a Kohonen neural network (KNN) approach to not only process "still" frames but also process video in real time. Experimental results demonstrated that it is possible to provide real time "point-outs" of thermally significant objects.


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    Titel :

    Neural network real time video processor for early aircraft detection


    Beteiligte:
    Hauser, Gregory (Autor:in) / Manic, Milos (Autor:in)


    Erscheinungsdatum :

    2009


    Format / Umfang :

    4 Seiten, 10 Quellen




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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