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In this paper we present a cascade-based framework for object detection in which the node classifiers are trained by a learning algorithm based on ranking instead of classification error. Such an approach is particularly suited for facing the asymmetry between positive and negative class, that is a huge problem in object detection applications. Other methods focused on this problem and previously...
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