Abstract
In this paper, we present a description of an implemented system for the recognition of printed and handwritten postal addresses, based on Artificial Neural Networks (ANNs). Two classification methods were compared for the task of character and address recognition. We compared two neural network techniques, measuring recognition rate and accuracy. The C programming language, a SUN workstation, and the SP2 Supercomputer were used for the experiments. The system has been successfully tested on real world printed and handwritten postal addresses. Some experimental results are presented in this paper.
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© 1998 Springer-Verlag London
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Blumenstein, M., Verma, B. (1998). A Neural Network for Real-World Postal Address Recognition. In: Chawdhry, P.K., Roy, R., Pant, R.K. (eds) Soft Computing in Engineering Design and Manufacturing. Springer, London. https://doi.org/10.1007/978-1-4471-0427-8_9
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DOI: https://doi.org/10.1007/978-1-4471-0427-8_9
Publisher Name: Springer, London
Print ISBN: 978-3-540-76214-0
Online ISBN: 978-1-4471-0427-8
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