Florence Cloppet

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This paper presents a method of overlapping/aggregating nuclei cells segmentation. This method is based on the watershed segmentation algorithm, but the specificity of this work is to introduce some prior information about the usual shape of normal/pathological nuclei cells. Such prior information will help to optimize the right set of markers, from which(More)
This paper presents a fast method using simple genetic algorithms (GAs) for features selection. Unlike traditional approaches using GAs, we have used the combination of Adaboost classifiers to evaluate an individual of the population. So, the fitness function we have used is defined by the error rate of this combination. This approach has been implemented(More)
This paper presents a generic features selection method and its applications on some document analysis problems. The method is based on a genetic algorithm (GA), whose tness function is deened by combining Adaboot classiiers associated with each feature. Our method is not linked to a classiier achieving the-nal recognition task; we have used a combination(More)