Optimization Framework for a Multiple Classifier System with Non-Registered Targets
نویسندگان
چکیده
A fundamental problem facing the designers of automatic target recognition (ATR) systems is how to deal with out-of-library or non-registered targets. This research extends a mathematical programming framework that selects the optimal classifier ensemble and fusion method across multiple decision thresholds subject to classifier performance constraints. The extended formulation includes treatment of exemplars from target classes on which the ATR system is not trained (non-registered targets).
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