Fabien Carmagnac

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This paper deals with supervised document image classification. An original distance based strategy allows automatic feature selection. The computation of a distance between an image to be classified and a class representative (point of view) allows to estimate a membership function for all classes. The choice of the best point of view performs the feature(More)
This paper presents a semi-supervised document image classification system that aims to be integrated into a commercial document reading software. This system is asserted like an annotation help. From a set of unknown document images given by a human operator, the system computes regrouping hypothesis of same physical layout images and proposes them to the(More)
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