There is growing interest in applying machine learning algorithms to target acquisition tasks. Current algorithm studies suggest pixels on target area (POT) of 50-70, 150, 250, and 350 are adequate for detection, classification, recognition, and identification of tank-sized targets respectively. Using simple analyzes, we compare POT to Night Vision Integrated Performance Model (NV-IPM) range probability predictions for a typical LWIR sensor.


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    Title :

    Comparing pixels on target with NV-IPM range predictions


    Contributors:

    Conference:

    Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIV ; 2023 ; Orlando, Florida, United States


    Published in:

    Proc. SPIE ; 12533


    Publication date :

    2023-06-14





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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