Interfacing Kera’s deep learning technique for Real-Time Age and Gender Prediction

The 21st century has seen the humans achieved many unimaginable achievements in the world of technology. This technology can be used in a different way as individual desire. It can be used to identify a person’s age and also identify the gender of a particular person by detecting face of the person with help of a camera image or even with a real time video. In this research paper, a complete procedure, what are the different methodologies and algorithms that can be used, and which one is more accurate method to be used will be shown. The aim of this work is designing as well developing model which can detect faces thereby predict the age and gender from real time images. This model can be used in police surveillance, policing to dating applications and much more. Deep learning techniques are used in designing this model. Convolution neural network and computer vision is also being used in this paper to adapt to real time processing. Convolutional neural network along with the computer vision and keras is used in training the model. After extensive testing and training, accuracy of 85 percent is achieved for the developed model. This model can be broadly used in airports, age restricted areas or buildings and can be used in restricting the alcohol access to the under aged people.