911 resultados para foreground background segmentation
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Describe la agenda de la proxima reunion, comenta temas de esa agenda en los que hay programas previstos o en ejecucion, y enumera elementos del programa de trabajo de la Oficina de Estadistica de las NU sobre los cuales la Comision debe tomar decisiones.
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Human intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.
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Incluye Bibliografía
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Includes bibliography
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Incluye Bibliografía
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Pós-graduação em Ciência da Computação - IBILCE
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Incluye Bibliografía