How Transferable are CNN-based Features for Age and Gender Classification?

Preprint English OPEN
Özbulak, Gökhan; Aytar, Yusuf; Ekenel, Hazım Kemal;
  • Subject: Computer Science - Computer Vision and Pattern Recognition

Age and gender are complementary soft biometric traits for face recognition. Successful estimation of age and gender from facial images taken under real-world conditions can contribute improving the identification results in the wild. In this study, in order to achieve ... View more
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