Deep Learning Model for Gender and Age Detection

Abstract

Age and gender, two significant facial attributes, wield considerable influence within society. The automation of age and gender recognition holds substantial promise across a spectrum of real-world applications, including customer service, priority voting systems, medical diagnosis, and human-computer interaction. Leveraging deep learning techniques has emerged as a common thread in many research endeavours, yielding noteworthy performance enhancements. The integration of diverse deep learning models, coupled with an assessment of accuracy improvements, paves the way for further exploration. The central objective of this paper is to meticulously scrutinize age and gender recognition across various datasets and deep learning models. The paper expounds upon the advancements achieved in this domain, accentuating the contributions made. It outlines the models and datasets employed and rigorously evaluates