Facial Age Classification Using Deep Learning and Generative Adversarial Networks

This research focuses on improving the process of estimating facial age from photos using deep learning and a concept known as generative adversarial networks. The proposed method in this work focuses on the preprocessing phase in which an image quality enhancer is introduced to improve the resolution of a given photo before predicting the subject's facial age. As discussed in this dissertation, several real-life applications such as access control devices, biometrics devices, digital marketing software could potentially make use of the proposed facial age estimator.