Handwritten Character Recognition by using Convolutional Deep Neural Network; Review
Baki Koyuncu, Hakan Koyuncu · DergiPark (Istanbul University) · 2019
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.