Deep feature learning for gender classification with covered/camouflaged faces

Deep feature learning for gender classification with covered/camouflaged faces

The great attention to gender classification is increasing recently as genders carry rich information related to male and female social activities. Extracting discriminating visual representations for gender classification is challenging especially with covered or camouflaged faces. In this work, th...

Full description

Bibliographic Details
Main Authors: Mohammed Alghaili, Zhiyong Li, Hamdi A.R. Ali
Format: Article
Language:English
Published: Wiley 2020-12-01
Series:IET Image Processing
Subjects:
deep feature
gender classification
male activities
female social activities
covered camouflaged faces
variational feature learning loss function
Online Access:https://doi.org/10.1049/iet-ipr.2020.0199

Internet

https://doi.org/10.1049/iet-ipr.2020.0199

Similar Items