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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(5)
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10(1)
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014(1)
2014 International Work Conference on Bio-Inspired Intelligence: Intelligent Systems for Biodiversity Conservation, IWOBI 2014 - Proceedings(1)
Computer Methods and Programs in Biomedicine(1)
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scopus(16)
Compactly supported graph building for spectral clustering
Conference ObjectAbstract: In spectral clustering approaches is of great importance how is built the graph representation overPalabras claves:Autores:A. E. Castro-Ospina, Álvarez-Meza A.M., Castellanos-Dominguez G.Fuentes:scopusAutomatic graph building approach for spectral clustering
Conference ObjectAbstract: Spectral clustering techniques have shown their capability to identify the data relationships usingPalabras claves:Graph analysis, kernel function, Spectral clusteringAutores:A. E. Castro-Ospina, Álvarez-Meza A.M., Castellanos-Dominguez G.Fuentes:scopusAutomatic graph pruning based on kernel alignment for spectral clustering
ArticleAbstract: Detection of data structures in spectral clustering approaches becomes a difficult task when dealingPalabras claves:Graph pruning, Kernel alignment, Spectral clusteringAutores:A. E. Castro-Ospina, Álvarez-Meza A.M., Castellanos-Dominguez G.Fuentes:scopusAn improved multi-class spectral clustering based on normalized cuts
Conference ObjectAbstract: In this work, we present an improved multi-class spectral clustering (MCSC) that represents an alterPalabras claves:Autores:Acosta-Medina C.D., Castellanos-Dominguez G., Diego Hernán Peluffo-OrdóñezFuentes:scopusA kernel-based representation to support 3D MRI unsupervised clustering
Conference ObjectAbstract: A new kernel-based image representation is proposed on this paper aiming to support clustering tasksPalabras claves:Autores:A. E. Castro-Ospina, Álvarez-Meza A.M., Cardenas-Pena D., Castellanos-Dominguez G., Orbes-Arteaga M.Fuentes:scopusA novel color-based data visualization approach using a circular interaction model and dimensionality reduction
Conference ObjectAbstract: Dimensionality reduction (DR) methods are able to produce low-dimensional representations of an inpuPalabras claves:data visualization, Dimensionality reduction, Interactive Interface, Pairwise similarityAutores:Ana C. Umaquinga-Criollo, Castellanos-Dominguez G., Diego Fernando Peña-Unigarro, Diego Hernán Peluffo-Ordóñez, Javier E. Revelo-Fuelagán, Paul D. Rosero-Montalvo, Salazar-Castro J.A., Zenaida Castillo-MarreroFuentes:scopusGeneralized Low-Computational Cost Laplacian Eigenmaps
Conference ObjectAbstract: Dimensionality reduction (DR) is a methodology used in many fields linked to data processing, and maPalabras claves:Dimensionality reduction, Generalized methodology, Kernel approximations, Low-computational cost, multiple kernel learning, Spectral methodsAutores:Basante C., Castellanos-Dominguez G., Cruz-Cruz L.D., Diego Hernán Peluffo-Ordóñez, Javier E. Revelo-Fuelagán, Ortega C., Peña D.F., Salazar-Castro J.A., Xiomara P. Blanco-ValenciaFuentes:scopusNonparametric density-based clustering for cardiac arrhythmia analysis
Conference ObjectAbstract: In this work, a nonsupervised algorithm for feature selection and a non-parametric density-based cluPalabras claves:Autores:Castellanos-Dominguez G., Cuesta-Frau D., Diego Hernán Peluffo-Ordóñez, Rodríguez-Sotelo J.L.Fuentes:scopusNormalized cuts clustering with prior knowledge and a pre-clustering stage
Conference ObjectAbstract: Clustering is of interest in cases when data are not labeled enough and a prior training stage is unPalabras claves:Autores:A. E. Castro-Ospina, Acosta-Medina C.D., Castellanos-Dominguez G., Chavez-Chamorro D., Diego Hernán Peluffo-OrdóñezFuentes:scopusImage segmentation based on multi-kernel learning and feature relevance analysis
Conference ObjectAbstract: In this paper an automatic image segmentation methodology based on Multiple Kernel Learning (MKL) isPalabras claves:Kernel learning, Relevance analysis, Spectral clusteringAutores:Álvarez-Meza A.M., Castellanos-Dominguez G., Diego Hernán Peluffo-Ordóñez, Molina-Giraldo S.Fuentes:scopus