Development of signature recognition system using VGG16
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Published:2023
Issue:3
Volume:26
Page:807-813
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ISSN:0972-0529
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Container-title:Journal of Discrete Mathematical Sciences & Cryptography
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language:
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Short-container-title:JDMSC
Author:
Moud Deepak,Saxena Rakesh Kumar
Abstract
The goal of this research is to locate a signature recognition system that can replace individual presence in the process of handwritten signature recognition. It has been discovered that an automatic signature recognition system that does not require a person’s physical presence is necessary throughout corona duration. In this article more accurate signature recognition model employing VGG 16 pre- trained models is proposed. Novel Convolution neural network has exhibited 83% validation accuracy on the GPDS synthetic Signature dataset[1].
Publisher
Taru Publications
Subject
Applied Mathematics,Algebra and Number Theory,Analysis