Our model consists of five layers i.e. two convolution-pooling layers with 20 and 40 feature maps respectively and two-by-two max-pooling and one fully-connected hidden layer with 100 neurons.
Processed handwritten images to resemble the images of training-set.
Our model takes images of handwritten text as input and predicts the output.