HANDWRITTEN CHARACTER RECOGNITION SYSTEM USING ARTIFICIAL NEURAL NETWORKS
Pelin Görgel, Oğuzhan Öztaş · DergiPark (Istanbul University) · 2012
In this paper, a Handwritten Character Recognition system is designed using Multilayer Feedforward Articial Neural Networks. Backpropagation Learning algorithm is prefered for training of neural network. Training set occures of various Latin characters collected from different people. The characters are presented directly to the network and correctly sized in pre-processing. Recognition percentage of the system is higher than acceptable level. Input datas, network parametres and training period effect the result.