A Neural Network Based Character Recognition System Using Double Backpropagation - Kamruzzaman, Joarder; M. Aziz, d S. (Malaysian Journal of Computer Science, 1998)
Proposes a neural network based invariant character recognition system using double backpropagation network. The model consists of two parts. The first is a preprocessor which is intended to produce a translation, rotation and scale invariant representation of the input pattern. The second is a neural net classifier. The outputs produced by the preprocessor at the first stage are classified by this neural net classifier trained by a learning algorithm called double backpropagation. The recognition system was tested with ten numeric digits (0 9). The test included rotated, scaled and translated version of exemplar patterns. This simple recognizer with double backpropagation classifier could successfully recognize nearly 97% of the test patterns.