Deep Learning Based Approach for Gender Classification

Abstract

Face classification is a challenging task which has a vital role in many applications. Automatic classification of gender in face images has increasing amount of applications contributing particularly since the hike of social platforms and social media. In this Paper we classify the facial images according to their gender by constructing a deep convolution neural network (CNN), a significant performance and accuracy can be obtained. We propose a convolution neural network architecture that can be used even when the amount of data is large. Performance accuracy of the proposed network is tested on the LFW dataset (13,233 images of 5,749 subjects).