Documentos de Rodríguez-Sotelo J.L. | REDI

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Mostrando 4 resultados de: 4

Filtros aplicados

Área temáticas: "Métodos informáticos especiales"

Subtipo de publicación

Conference Object(3)

Publisher

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(3)

Área temáticas

Fisiología humana(2)

Ciencias de la computación(1)

Economía financiera(1)

Farmacología y terapéutica(1)

Funcionamiento de bibliotecas y archivos(1)

Área de conocimiento

Ciencias de la computación(3)

Aprendizaje automático(2)

Optimización matemática(1)

Simulación por computadora(1)

Año de Publicación

Origen

Palabras Claves

Eigenvectors(1)

Feature Extraction(1)

Graph-based clustering(1)

Kernel spectral clustering(1)

Automatic motion segmentation via a cumulative kernel representation and spectral clustering

Conference Object

Abstract: Dynamic or time-varying data analysis is of great interest in emerging and challenging research on a

Palabras claves:

Kernel spectral clustering, Motion segmentation, Time-varying data, Variable ranking

Ana C. Umaquinga-Criollo, Diego Hernán Peluffo-Ordóñez, Luis Suárez-Zambrano, O. T. Sánchez-Manosalvas, Omar R. Oña-Rocha, Paul D. Rosero-Montalvo, Rodríguez-Sotelo J.L.

Automatic sleep stages classification using EEG entropy features and unsupervised pattern analysis techniques

Abstract: Sleep is a growing area of research interest in medicine and neuroscience. Actually, one major conce

Palabras claves:

Clustering, Feature Extraction, feature selection, Q-α, Relevance analysis, Signal entropy, Sleep stages

Cirugeda-Roldán E., Cuesta-Frau D., Diego Hernán Peluffo-Ordóñez, Jiménez-Rodríguez A., Osorio-Forero A., Rodríguez-Sotelo J.L.

Developments on solutions of the normalized-cut-clustering problem without eigenvectors

Conference Object

Abstract: Normalized-cut clustering (NCC) is a benchmark graph-based approach for unsupervised data analysis.

Palabras claves:

Eigenvectors, Graph-based clustering, Normalized cut clustering, Quadratic forms

A. E. Castro-Ospina, Diego Hernán Peluffo-Ordóñez, Israel D. Herrera-Granda, K. L. Ponce-Guevara, Leandro L. Lorente-Leyva, Miguel A. Becerra, Paul D. Rosero-Montalvo, Rodríguez-Sotelo J.L.

Sleep stages clustering using time and spectral features of EEG signals an unsupervised approach

Conference Object

Abstract: Sleep stage classification is a highly addressed issue in polysomnography; It is considered a tediou

Palabras claves:

Diego Hernán Peluffo-Ordóñez, Jiménez-Rodríguez A., Jorge Serrano, Osorio-Forero A., Restrepo-De-Mejía F., Rodríguez-Sotelo J.L.