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The DSFPN, a new neural network for optical character recognition

Lookup NU author(s): Ian Morns, Emeritus Professor Satnam Dlay

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Abstract

A new type of neural network for recognition tasks is presented in this paper. The network, called the dynamic supervised forward-propagation network (DSFPN), is based on the forward only version of the counterpropagation network (CPN). The DSFPN, trains using a supervised algorithm and can grow dynamically during training, allowing subclasses in the training data to be learnt in an unsupervised manner. It is shown to train in times comparable to the CPN while giving better classification accuracies than the popular backpropagation network. Both Fourier descriptors and wavelet descriptors are used for image preprocessing and the wavelets are proven to give a far better performance. © 1999 IEEE.

Publication metadata

Author(s): Morns IP, Dlay SS

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Neural Networks

Year: 1999

Volume: 10

Issue: 6

Pages: 1465-1473

Print publication date: 01/01/1999

ISSN (print): 1045-9227

ISSN (electronic): 1941-0093

Publisher: IEEE

URL: http://dx.doi.org/10.1109/72.809091

DOI: 10.1109/72.809091

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