Detecting Sex From Handwritten Examples

Abstract

There are several tasks that human excel at and computers do not and vice-versa. Just until a few years ago computers were as good as a storage for images and videos. However, in the past 6 years with the boon in artificial neural network, labeled data and computation power; machines have started becoming smart at tasks like recognizing images, detecting different objects in images, captioning images, understanding and summarizing videos, detecting semantic actions in videos and so on. Deep learning researchers and practitioners have started demonstrating notable performance of AI(Artificial Intelligence) on many different tasks that pushes the boundaries and as a continuation of that process, we took one specific problem to solve using deep learning that even human can not solve. We have taken Bangla handwritten characters, then trained them applying several deep learning techniques such as Convolutional Neural Network and Recurrent Neural Network to predict the sex of the writer. Consequently, we have got 91.85% accuracy rate and also demonstrated further analysis of the results that we got.