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Penacée: a neural net system for recognizing on-line handwriting

Guyon, I.; Bromley, J. M.; Matić, N.; Schenkel, M. and Weissman, H. (1996). Penacée: a neural net system for recognizing on-line handwriting. In: Domany, E.; Van Hemmen, J. L. and Schulten, K. eds. Models of Neural Networks III: Association, Generalization and Representation. Physics of Neural Networks, 3. New York: Springer, pp. 255–279.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1007/978-1-4612-0723-8_7
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Abstract

We report on progress in handwriting recognition and signature verification. Our system, which uses pen-trajectory information, is suitable for use in pen-based computers. It has a multi-modular architecture whose central trainable module is a time-delay neural network. Results comparing our system and a commercial recognizer are presented. Our best recognizer makes three times less errors on hand-printed word recognition than the commercial one.

Item Type: Book Section
Copyright Holders: 1996 Springer-Verlag New York, Inc.
ISBN: 0-387-94368-4, 978-0-387-94368-8
Keywords: handwriting recognition; neural networks; on-line handwriting recognition; signature verification; Time Delay Neural Network; hybrid systems; pen-based computers; cursive handwriting
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 35667
Depositing User: Jane M. Bromley
Date Deposited: 22 May 2013 11:38
Last Modified: 09 Dec 2018 11:25
URI: http://oro.open.ac.uk/id/eprint/35667
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