A Time Delay Neural Network character recognizer for a touch terminal.

I. Guyon, P. Albrecht, Y. Le Cun , J. Denker, and W. Hubbard.
In International Neural Network Conference , pages 42--45, Paris, France, IEEE.

We describe a system which can recognize digits and uppercase letters hand-printed on a touch terminal. A character is input as a sequence of [x(t), y(t)] coordinates, subjected to very simple preprocessing, and then classified by a trainable neural network. The classifier is analogous to ``time delay neural networks'' previously applied to speech recognition. The network was trained on a set of 12,000 digits and uppercase letters, from approximately 250 different writers, and tested on 2,500 such characters from other writers. Classification accuracy exceeded 96% on the test examples.

Keywords: character recognition, on-line character recognition, handwritten characters, neural networks, touch terminal, touch screen.

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