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Gender classification by LPQ features from intensity and Monogenic images

24-25 Nov. 2017
Tóm tắt: 

Facial biometrics systems struggle to find human biometrics cues from face images. These cues include identity, expression, age, pose and gender, to name a few. Compared with others, gender is among the most useful information since it can be used in human-machine interaction applications, marketing researches and advertising [1]. Unlike other attributes, gender has only two values, male and female, but gender recognition is one of the most challenging tasks [2].