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Many believe that gender classification is a solved problem, however, gender classification for children is a very difficult problem that has not been adequately addressed by the research community. In this work we demonstrate this fact and present a system that performs gender classification on children that outperforms humans. Motivated by the significant improvement in model selection for age estimation,...
Face age estimation is a difficult problem due to the dynamics of facial aging and its complex interactions owing to genetics and behavior factors. In this work we develop a robust age estimation system tuned by model selection that outperforms all prior systems on the FG-NET face database. We study various model selection methods systematically to determine the best selection methods among Least...
Age estimation from digital pictures of the face is a very promising research field that is now receiving wide attention. As with any good research problem, face age-estimation is wrought with many challenging interactions that cannot easily be separated out. In general, aging patterns are well understood for all humans, however, these patterns become confounded by intrinsic factors of genetics, gender...
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