FACE ASSESSMENT LEARNED FROM EXISTING IMAGES IN ORDER TO CLASSIFY THE GENDER OF THE IMAGES BASED ON IMPROVED FACE RECOGNITION
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Abstract
Face is among the most vital biometric traits. When we study the face, we can gather details
such as age and gender, ethnicity, expression, identity, etc. A system for gender classification
uses the faces of people from an image to identify what nature of the gender (male/female)
that is the individual. A gender-based approach that is successful can improve the
performance of numerous other applications, including facial recognition and a sophisticated
human-computer interface. This paper provides the fundamental processing steps required for
gender classification based on face images. In this paper, a variety of techniques employed in
different stages in gender categorization, i.e., features extraction as well as classification are
presented and contrasted.
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