Signature Verification Using a "Siamese" Time Delay Neural Network
Abstract
This paper describes an algorithm for verification of signatures written on a pen-input tablet. The algorithm is based on a novel, artificial neural network, called a "Siamese" neural network. This network consists of two identical sub-networks joined at their out(cid:173) puts. During training the two sub-networks extract features from two signatures, while the joining neuron measures the distance be(cid:173) tween the two feature vectors. Verification consists of comparing an extracted feature vector ~ith a stored feature vector for the signer. Signatures closer to this stored representation than a chosen thresh(cid:173) old are accepted, all other signatures are rejected as forgeries.
Cite
Text
Bromley et al. "Signature Verification Using a "Siamese" Time Delay Neural Network." Neural Information Processing Systems, 1993.Markdown
[Bromley et al. "Signature Verification Using a "Siamese" Time Delay Neural Network." Neural Information Processing Systems, 1993.](https://mlanthology.org/neurips/1993/bromley1993neurips-signature/)BibTeX
@inproceedings{bromley1993neurips-signature,
title = {{Signature Verification Using a "Siamese" Time Delay Neural Network}},
author = {Bromley, Jane and Guyon, Isabelle and LeCun, Yann and Säckinger, Eduard and Shah, Roopak},
booktitle = {Neural Information Processing Systems},
year = {1993},
pages = {737-744},
url = {https://mlanthology.org/neurips/1993/bromley1993neurips-signature/}
}