Image processing to accomplish automatic recognition of military vehicles has promised increased weapons systems effectiveness and reduced timelines for a number of Department of Defense missions. Automatic Target Recognizers (ATR) are often claimed to be able to recognize many different ground vehicles as possible targets in military air-to- surface targeting applications. The targeting scenario conditions include different vehicle poses and histories as well as a variety of imaging geometries, intervening atmospheres, and background environments. Testing these ATR subsystems in most cases has been limited to a handful of the scenario conditions of interest, as is represented by imagery collected with the desired imaging sensor. The question naturally arises as to how robust the performance of the ATR is for all scenario conditions of interest, not just for the set of imagery upon which an algorithm was trained.


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    Title :

    System transfer modelling for automatic target recognizer evaluations


    Contributors:

    Conference:

    Automatic Object Recognition ; 1991 ; Bellingham,Washington,United States


    Published in:

    Proc. SPIE ; 10307


    Publication date :

    1991-11-01




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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