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This paper addresses one of the fundamental problems encountered in performance prediction for object recognition. In particular we address the problems related to estimation of small gallery size that can give good error estimates and their confidences on large probe sets and populations. We use a generalized two-dimensional prediction model that integrates a hypergeometric probability distribution...
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