Age and Gender Classification Using Convolutional Neural Network

Abstract

Abstract: Now a days Age and gender are two crucial facial traits that influence social relationships. Human age and gender are determined by identifying facial images. This research focuses mostly on real-time applications like biometric verification and aging analysis. Age groups include child, young, adult, and old. Gender classification is the process of classifying males and females based on face images. CNN is used to classify people by their age and gender. CNN (Convolutional Neural Network) is used for analyzing visual data. CNN models are a superior type of image classification that, when compared to support vector machine performance on the dataset, where the UTK Face, Tuftes face dataset has 15171 photos, in order to increase the heterogeneity of the training and facial recognition on the dataset.