GitHub repository: shourya27/Handwriting-Recognition
Description: Handwriting recognition (HWR), also known as Handwritten Text Recognition (HTR), is the ability of a computer to receive and interpret intelligible handwritten input from sources such as paper documents, photographs, touch-screens and other devices. For this task we build a convolution neural network (CNN) in Keras using Tensorflow backend. We will use a standard CNN with multiple convolution and maxpool layers, a few dense layers and a final output layer with softmax activation. RELU activation was used between the convolution and dense layers and model was optimized using Adam optimizer. The size of the model needs to be proportional to the size of the data. Three blocks of convolution -maxpool layers and couple of dense layers was sufficient for this problem.