Handwritten Devanagari Character Classification using Deep Learning

Since past few years, deep neural networks, because of their outstanding performance, are getting highly used in computer vision and machine learning tasks such as regression, segmentation, classification, detection, pattern recognition etc. Recognition of handwritten Devanagari characters is challenging task, but Deep learning can be effectively used as a solution for various such problems. Person to person variations in writing style makes handwritten character recognition one of the most difficult tasks. In this Experiment, we successfully tried to classify handwritten Devanagari characters using transfer learning mechanism with the help of Alexnet. Alexnet, a convolutional neural network, is trained over a dataset of around 16870 samples of 22 consonants of Devanagari script which shows impressive results. The transfer learning helps to learn faster and better even if the data samples are less as compared with the training a CNN from scratch.