Human Recognition Model Using CNN

Since the ever increasing demand of social platforms and social media, it is highly recommended to check age and gender of the person using social websites to avoid any age restricted content. Recognition of age and gender can be used in variety of applications majorly authentication, visual surveillance, customer care, biometrics. A convolutional neural network (CNN) is an emerging tool for image processing and human identification. In this paper, deep- convolutional neural networks (CNN) is proposed to estimate structures of human's face and hence improve performance for recognition of human's gender and age significantly. Here, we propose a less complex convolutional neural network design which can be effectively used in case of a small amount of learning data. With small learning data, the automatic age and gender recognition model is proposed here which gives better dropout rate with latest benchmark given by Adience.