Signature recognition using conjugate gradient neural networks

DOI

10.2991/jcis.2006.271How to use a DOI?

Keywords

Signature Verification, MATLAB Software, Conjugate Gradient, Segmentation, Skilled Forgery, and Genuine.

Abstract

SIGNATURE RECOGNITION USING CONJUGATE GRADIENT NEURAL NETWORKS Transforming the input before training yields much lower error, but is more sensitive. Most importantly, we have presented system can vary in security depending on the situation. Uses for such a system range from securing a credit card transaction at the point of sale to user authentication on tablet PCs. We hope that this system will help future research in creating variable security HSV systems as well as systems which can select feature sets which are optimal for a specific user.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jamal Abu Hasna
PY  - 2006/10
DA  - 2006/10
TI  - Signature recognition using conjugate gradient neural networks
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.271
DO  - 10.2991/jcis.2006.271
ID  - AbuHasna2006/10
ER  -