Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/15077
Título: A performance based study on gender recognition in large datasets
Autores/as: Díaz Cabrera, Moisés 
Lorenzo Navarro, José Javier 
Castrillón-Santana, Modesto 
Clasificación UNESCO: 120304 Inteligencia artificial
Palabras clave: Gender recognition
BEFIT
Classiffier fusion
LFW
MORPH
Fecha de publicación: 2012
Resumen: Gender recognition has achieved impressive results based on the face appearance in controlled datasets. Its application in the wild and large datasets is still a challenging task for researchers. In this paper, we make use of classical techniques to analyze their performance in controlled and uncontrolled condition respectively with the LFW and MORPH datasets. For both sets the benchmarking protocol follows the 5-fold cross-validation proposed by the BEFIT challenge.
URI: http://hdl.handle.net/10553/15077
Fuente: VI Jornadas de Reconocimiento Biométrico de Personas (JRBP12). Las Palmas de Gran Canaria. 2012
Colección:Actas de congresos
miniatura
Artículo
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Este elemento está sujeto a una licencia Licencia Creative Commons Creative Commons