Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/16994
Título: Gender and identity classification for a naive and evolving system
Autores/as: Castrillón-Santana, Modesto 
Déniz Suárez, Oscar
Lorenzo Navarro, José Javier 
Hernández Tejera, Francisco Mario 
Clasificación UNESCO: 120304 Inteligencia artificial
Fecha de publicación: 2006
Resumen: This paper does not propose a new technique for face representationorclassification. Insteadtheworkdescribed here investigates the evolution of an automatic system which, based on a currently common framework, and starting from an empty memory, modifies its classifiers according to experience. In the experiments we reproduce up to a certain extent the process of successive meetings. The results achieved, even when the number of different individuals is still reduced compared to off-line classifiers, are promising.
URI: http://hdl.handle.net/10553/16994
Fuente: <p>Second International Workshop on Multimodal User Authentication</p>
Colección:Actas de congresos
miniatura
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