Recognition of Persian handwritten digits using image profiles of multiple orientations
Pattern Recognition Letters
Robust Handwritten Character Recognition with Features Inspired by Visual Ventral Stream
Neural Processing Letters
The use of radon transform in handwritten Arabic (Indian) numerals recognition
WSEAS Transactions on Computers
Precise and accurate decimal number recognition using Global Motion Estimation
International Journal of Artificial Intelligence and Soft Computing
Offline arabic handwritten text recognition: A Survey
ACM Computing Surveys (CSUR)
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The paper introduces a method of finding the neighborhood of the optimal number of hidden neurons for an error back propagation neural network with a single hidden layer. It is based on a study of the curvature of the error function, during the training phase of the network.The method assures convergence and bypasses local minimas. Experimental results show the uniqueness of the method's solution regardless of the initial values of the network's parameters. Two neural networks were built, one for recognizing unconstrained handwritten English numerals and the other for Arabic numerals. Recognition results and comparison with other methods are also presented.