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.
Keywords :
CNN(Convolution neural network), Age Prediction, Gender Prediction, Biometric System, Face Detection