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Segmentation of Medical Images using Fuzzy Mathematical Morphology
Article
Article
Segmentation of Medical Images using Fuzzy Mathematical Morphology
Bouchet, A. et al · SEDICI UNLP · 2007
Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP). It allows processing images to enhance fuzzy areas, segment objects, detect edges and analyze structures. The techniqu...
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Acceso abiertoRuta libre sin proxy. Acceso recomendado cuando no hay suscripción activa.
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Evolving fuzzy systems : A new strategy for rule semantics preservation
Text / resource
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Evolving fuzzy systems : A new strategy for rule semantics preservation
Osella Massa, Germán Leandro et al · SEDICI UNLP · 2005
Fuzzy rule-based systems have proved to be a convenient tool for modeling complex systems. This is due to their capacity to capture their typical imprecision, which makes classical methods inefficient. At present, Fuzzy...
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Acceso abiertoRuta libre sin proxy. Acceso recomendado cuando no hay suscripción activa.
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Fractional Brownian Motions, Fractional Noises and Applications
Article
Article
Fractional Brownian Motions, Fractional Noises and Applications
Benoît B. Mandelbrot; John W. Van Ness · SIAM Review · 1968
Previous article Next article Fractional Brownian Motions, Fractional Noises and ApplicationsBenoit B. Mandelbrot and John W. Van NessBenoit B. Mandelbrot and John W. Van Nesshttps://doi.org/10.1137/1010093PDFBibTexSecti...
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El enlace apunta a material asociado, anexos, tablas, datos o página complementaria. No se marca como libro/texto completo.
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Clustering by Passing Messages Between Data Points
Article
Article
Clustering by Passing Messages Between Data Points
Brendan J. Frey; Delbert Dueck · Science · 2007
Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such "exemplars" can be found by randomly choosing an initial subset of data ...
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Data clustering
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Data clustering
Anil K. Jain; M. Narasimha Murty; Patrick J. Flynn · ACM Computing Surveys · 1999
Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has been addressed in many contexts and by researchers in many disci...
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El enlace apunta a material asociado, anexos, tablas, datos o página complementaria. No se marca como libro/texto completo.
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