Offline handwritten signature verification through network radial basis functions optimized by Differential Evolution. De Medeiros Nápoles, S. & Zanchettin, C. In Proceedings of the International Joint Conference on Neural Networks, 2012.
abstract   bibtex   
The handwritten signature is present in all important documents. In law, if the signature on a document is false, this document is also considered a fraud. This paper uses a neural network of radial basis function optimized by Differential Evolution Algorithm with features that best discriminates between a genuine signature of a simulated forgery. The experiments with this promising technique were made with a GPDS-300gray images base and the results subjected to statistical tests with the performance of technical literature. © 2012 IEEE.
@inproceedings{
 title = {Offline handwritten signature verification through network radial basis functions optimized by Differential Evolution},
 type = {inproceedings},
 year = {2012},
 identifiers = {[object Object]},
 keywords = {Differential Evolution,Handwritten Signature,Off-line Verification,Radial Basis Function},
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 created = {2019-02-14T18:02:00.156Z},
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 abstract = {The handwritten signature is present in all important documents. In law, if the signature on a document is false, this document is also considered a fraud. This paper uses a neural network of radial basis function optimized by Differential Evolution Algorithm with features that best discriminates between a genuine signature of a simulated forgery. The experiments with this promising technique were made with a GPDS-300gray images base and the results subjected to statistical tests with the performance of technical literature. © 2012 IEEE.},
 bibtype = {inproceedings},
 author = {De Medeiros Nápoles, S.H.L. and Zanchettin, C.},
 booktitle = {Proceedings of the International Joint Conference on Neural Networks}
}

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