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NiohSign: A Siamese Neural Network Approach for Signature Authentication

Effiok, Anthony (2020) NiohSign: A Siamese Neural Network Approach for Signature Authentication. Masters thesis, Dublin, National College of Ireland.

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Signatures continuously play important roles as an accurate means of identification and also as a means to verify permissions given for tasks. The process of verifying if an appended signature for a task is forged or genuine plays a largely important role when trying to prevent acts relating to fraud or worse impersonation.
Objective- This project aims to create a network that is capable of identifying if a signature is forged or authentic through the use of Siamese neural networks which is essentially a twin neural network.
Methodology- The network to be used a s the base network is a model of the ResNet network known as InceptionResNetV2 model. The dataset used is a signature dataset that contains the signatures of 260 individuals with 100 in Bengali and 160 in Hindi.
Results- The Model is tested on the signatures appended in Hindi and is seen to perform well with an accuracy of 81.71%.
Keywords - Signature authentication, Siamese neural network, Artificial neural network

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Dan English
Date Deposited: 20 Jan 2021 13:55
Last Modified: 20 Jan 2021 13:55

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