Abstract
On the basis of recent binary signal detection theory (BSDT), optimal recognition algorithms for complex images are constructed and their optimal performance are calculated. A methodology for comparing BSDT predictions and measured human performance is developed and applied to explaining particular face recognition experiment. The BSDT makes possible computer codes with recognition performance better than that in humans, its fundamental discreteness is consistent with the experiment. Related neurobiological and behavioral effects are briefly discussed.
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