Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/95659
Type: Artigo de evento
Title: Neural Approaches For Human Signature Verification
Author: Lee Luan Ling
Abstract: This paper describes three neural network (NN) based approaches for on-line human signature verification: Bayes multilayer perceptrons (BMP), time-delay neural networks (TDNN), input-oriented neural networks (IONN). The backpropagation algorithm was used for the network training. A signature is input as a sequence of instantaneous absolute velocity (|v(t)|) extracted from a pair of spatial coordinate time functions (x(t), y(t)). The BMP provides the lowest misclassification error rate among three types of networks.
Editor: IEEE, Piscataway, NJ, United States
Rights: fechado
Identifier DOI: 
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-0030397863&partnerID=40&md5=8d505ae90e8e260ac1539aa9377ed969
Date Issue: 1996
Appears in Collections:Unicamp - Artigos e Outros Documentos

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