AGE ESTIMATION AND GENDER CLASSIFICATION TECHNIQUES USING CNN: A SURVEY

Abstract

Now a days Researchers have given more interest in soft biometrics area to fill the communication gaps between humans and machines. Soft-biometric consists of age, gender (sex), ethnicity, height, facial measurements and etc. The real- world application of computer vision has grown in recent years. This survey paper contains a detailed discussion about the contribution of the researchers in the area of age estimation and gender classification using CNN (Convolutional Neural Network). Different neural network model features, such as datasets, methodology, discoveries, accuracy measures, and results, are presented for further research. In this survey paper, we also reviewed various age and gender recognition strategies and summarize the tasks for future research aspects. KEYWORDS— Soft Biometrics, Neural Network, CNN, Computer Vision, Gender recognition, Age estimation