Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/17812
Título: | Multi-scale score level fusion of local descriptors for gender classification in the wild | Autores/as: | Castrillón-Santana, Modesto Lorenzo Navarro, José Javier Ramón Balmaseda, Enrique José |
Clasificación UNESCO: | 120304 Inteligencia artificial | Palabras clave: | Soft biometrics Gender classification Local descriptors Score level fusion CNN |
Fecha de publicación: | 2017 | Publicación seriada: | Multimedia Tools and Applications | Resumen: | The 2015 FRVT gender classification (GC) report evidences the problems that current approaches tackle in situations with large variations in pose, illumination, background and facial expression. The report suggests that both commercial and research solutions are hardly able to reach an accuracy over 90% for The Images of Groups dataset, a proven scenario exhibiting unrestricted or in the wild conditions. In this paper, we focus on this challenging dataset, stepping forward in GC performance by observing: 1) recent literature results combining multiple local descriptors, and 2) the psychophysics evidences of the greater importance of the ocular and mouth areas to solve this task... | URI: | http://hdl.handle.net/10553/17812 | ISSN: | 1380-7501 | DOI: | 10.1007/s11042-016-3653-2 | Fuente: | Multimedia Tools and Applications [ISSN 1380-7501], v. 76 (4), p. 4695–4711 |
Colección: | Artículos |
Citas SCOPUSTM
16
actualizado el 02-feb-2025
Citas de WEB OF SCIENCETM
Citations
10
actualizado el 02-feb-2025
Visitas
114
actualizado el 13-abr-2024
Descargas
318
actualizado el 13-abr-2024
Google ScholarTM
Verifica
Altmetric
Comparte
Exporta metadatos
Este elemento está sujeto a una licencia Licencia Creative Commons