Real-Time Age and Gender Prediction

Age and gender identification have grown to be important components of the biometric system, protection, and care. People frequently use it to get ageappropriate content. Social media makes use of it to broaden the reach of multilayer advertising and promotions. Face detection has become so widely used that we need to improve it using a variety of techniques to get more accurate results. We have created a lightweight deep Convolution neural network model for age and generation prediction in this paper. Wiki, UTK Face and Adience datasets have been combined to create a single dataset of 18728 photos in order to increase the diversity of the training dataset. With this sizable mixed dataset, we were able to attain a real-time accuracy of 48.5980.76. several experimental studies