Authors
Samy S. Abu-Naser
North Dakota State University (PhD)
Abstract
Every person has his/her own unique signature that is used mainly for the purposes of personal identification and verification of important documents or legal transactions. There are two kinds of signature verification: static and dynamic. Static(off-line) verification is the process of verifying an electronic or document signature after it has been made, while dynamic(on-line) verification takes place as a person creates his/her signature on a digital tablet or a similar device. Offline signature verification is not efficient and slow for a large number of documents. To overcome the drawbacks of offline signature verification, we have seen a growth in online biometric personal verification such as fingerprints, eye scan etc. In this paper we created CNN model using python for offline signature and after training and validating, the accuracy of testing was 99.70%.
Keywords Handwritten  Verification  Signature
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Citations of this work BETA

Classification of Alzheimer’s Disease Using Traditional Classifiers with Pre-Trained CNN.Husam R. Almadhoun & Samy S. Abu-Naser - 2021 - International Journal of Academic Health and Medical Research (IJAHMR) 5 (4):17-21.
Detection and Classification of Gender-Type Using Convolution Neural Network.Husam R. Almadhoun - 2021 - International Journal of Academic Engineering Research (IJAER) 4 (12):15-20.
Apple Fruits Classification Using Deep Learning.Shawwa Mohammad - 2020 - International Journal of Academic Engineering Research (IJAER) 3 (12):1-6.
ANN for Tic-Tac-Toe Learning.Dalffa Abu-Mohaned - 2020 - International Journal of Engineering and Information Systems (IJEAIS) 3 (2):9-17.

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