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Handwritten character recognition is an important
domain of research with implementation in varied fields. Past and recent works in this field focus on
diverse languages to utilize the character recognition in automated data-entry
applications. Deep Neural network studies recognize the individual characters
in the form images. The reliance of each recognition, which is provided by the
neural network as part of the ranking result, is one of the things used to
customize the implementation to the request of the client. Convolutional Deep neural
network model is reviewed to recognize the handwritten characters in this
study. This model, initially, learned a useful set of support by using core and
local receptive areas and then a densely connected network layers are employed for
the discernment task.