FACE ASSESSMENT LEARNED FROM EXISTING IMAGES IN ORDER TO CLASSIFY THE GENDER OF THE IMAGES BASED ON IMPROVED FACE RECOGNITION

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N. Srivani, Dr Prasadu Peddi

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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How to Cite
N. Srivani, Dr Prasadu Peddi. (2022). FACE ASSESSMENT LEARNED FROM EXISTING IMAGES IN ORDER TO CLASSIFY THE GENDER OF THE IMAGES BASED ON IMPROVED FACE RECOGNITION. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(6), 5724–5735. https://doi.org/10.17762/turcomat.v12i6.12706
Section
Research Articles