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Mostrando ítems 61-70 de 1229
Randomized Methods For Higher-order Subspace Separation
(IEEENew York, 2016)
Desarrollo de una metodología como soporte para la detección de enfermedades vasculares del tejido conectivo a través de imágenes capilaroscópicas
(2010)
En este documento de tesis doctoral se presentan los resultados de una metodología para caracterizar y clasificar imágenes digitales de capilares en tres principales grupos: imágenes normales, imágenes con Lupus Eritematoso ...
Dimensionality Reduction for Automatic Pattern Recognition on BiosignalsReducción de dimensión para el reconocimiento automático de patrones sobre bioseñales
(Pereira : Universidad Tecnológica de PereiraFacultad de Ciencias Básicas, 2011)
Independent block identification in multivariate time series
(Wiley Blackwell Publishing, Inc, 2020-07)
In this-30 work we propose a model selection criterion to estimate the points of independence of a random vector, producing a decomposition of the vector distribution function into independent blocks. The method, based on ...
Kernel learning for robust dynamic mode decomposition: linear and nonlinear disambiguation optimization
(Royal Soc Chemistry, 2022)
Research in modern data-driven dynamical systems is typically focused on the three key challenges of high dimensionality, unknown dynamics and nonlinearity. The dynamic mode decomposition (DMD) has emerged as a cornerstone ...
Um método para seleção de atributos em bases de dados de classificação hierárquica multirrótulo
(Universidade Tecnológica Federal do ParanáPonta GrossaBrasilPrograma de Pós-Graduação em Ciência da ComputaçãoUTFPR, 2022-07-07)
Hierarchical multi-label classification problems usually need to deal with datasets that have a large number of attributes and labels, which can negatively interfere with the performance of the classifier. The application ...
Mapeamento isométrico de atributos baseado em geometria diferencial para aprendizado de métricas não supervisionado
(Universidade Federal de São CarlosUFSCarCâmpus São CarlosEngenharia de Computação - EC, 2021-11-16)
The act of representing a dataset in a way that’s more compact and significant is denominated dimensionality reduction. The capacity of building adaptive distance functions to each dataset before classification is known ...
Información discriminativa en clasificadores basados en modelos ocultos de Markov
(2011-03-09)
Hidden Markov models (HMM) are statistical models which can efficiently deal with sequential data. They provide a way to model complex dependencies between observed data by setting simple dependencies between latent ...
Descripción sintética de objetos en dos dimensiones de acuerdo a su contorno
(2008-10-20)
RESUMEN: En este trabajo se propone una técnica para la descripción sintáctica del contorno de figuras geométricas en dos dimensiones, por medio del análisis de puntos equidistantes sobre el contorno, se aplican criterios ...