The term handwriting recognition (HWR) refers to the ability of a computer to receive and interpret as text intelligible handwritten input from sources such as paper documents, photographs, and touchscreens. Written text can be detected on a piece of paper with optical scanning (optical character recognition (OCR)) or intelligent word recognition.
An autoencoder is a neural network, whose purpose is to code its input into small dimensions, and the result obtained helps to reconstruct the input itself. Autoencoders are made up of the union of the following two subnets: encoder and decoder. The encoder and the decoder will be differentiable with respect to the distance function, so the parameters of the encoding/decoding functions can be optimized to minimize the loss of reconstruction, using the gradient stochastic....
