Age and Gender Prediction from Facial Features Using Deep Learning

Abstract

Automatic age and gender classification has been significant to a rising variety of applications since the rise of social platforms and social media. The performance of existing algorithms on real-world images, on the other hand, is pathetically inadequate, especially when compared to the massive leaps in performance recently reported for the related task of facial recognition. In this paper, we show that learning representations with deep convolutional neural networks (CNN) can result in considerable improvements in performance on certain tasks [1]. We propose a simple convolutional net design that can be used even when learning data is scarce to do it.