Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/16240
Título: Learning to recognize gender using experince
Autores/as: Castrillón-Santana, Modesto 
Lorenzo Navarro, José Javier 
Freire-Obregón, David 
Déniz Suárez, Oscar
Clasificación UNESCO: 120304 Inteligencia artificial
Palabras clave: Facial analysis
Online learning
Gender
Fecha de publicación: 2010
Editor/a: Institute of Electrical and Electronics Engineers (IEEE) 
Proyectos: Tecnicas de Visión Para la Interacción en Entornos de Interior Con Elaboración Mapas Cognitivos en Sistemas Perceptuales Heterogéneos. 
Publicación seriada: Proceedings - International Conference on Image Processing 
Conferencia: IEEE International Conference on Image Processing 
Resumen: Automatic facial analysis abilities are commonly integratedin a system by a previous off-line learning stage. In this pa-per we argue that a facial analysis system would improve itsfacial analysis capabilities based on its own experience simi-larly to the way a biological system, i.e. the human system,does throughout the years. The approach described, focusedon gender classification, updates its knowledge according tothe classification results. The presented gender experiments suggest that this approach is promising, even when just a short simulation of what for humans would take years of acquisition experience was performed.
URI: http://hdl.handle.net/10553/53650
ISBN: 978-1-4244-7992-4
ISSN: 1522-4880
DOI: 10.1109/ICIP.2010.5653661
Fuente: Proceedings of 2010 IEEE 17th in Conference on Image Processing, ICIP (5653661), Hong Kong, China, september 26-29, ISSN 1522-4880, p. 4533-4536
Colección:Actas de congresos
miniatura
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