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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Issue: March 2023

Volume 8 | Issue 3

Impact factor: 8.15

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Paper Title: Online Signature Verification Using Neural Network
Authors Name: Rohan Dattatraya Gaidhani , Rushikesh Aaba Thombare , Aarti Navnath Ghorpade , Unnati Kantilal Jadhav , Ms.Sneha A. Khaire
Unique Id: IJSDR2303017
Published In: Volume 8 Issue 3, March-2023
Abstract: Biometrics is now widely used all over the world for the identification and verification of people and their signatures. A person’s handwritten signature is a unique identifying work of human that is primarily used and recognized in banking and other financial and legal operations. Handwritten signatures, on the other hand, are becoming increasingly valuable due to their historical significance as a target of deception. The Sign Verification System (SVS) tries to determine whether a sign is genuine (created by the specified individual) or forged (produced by an impostor).Using images of scanned signatures and other documents without dynamic information about the signing process has proven difficult, especially in offline (static) situations. The use of Deep Learning algorithms to learn feature signature picture representations has been well-documented in the literature over the last five to ten years. Here, we examine how the subject has been studied throughout the last few decades, as well as the most recent developments and future study plans
Keywords: Offline handwritten signature, classification, algorithms, artificial intelligence, CNN
Cite Article: "Online Signature Verification Using Neural Network", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 3, page no.82 - 85, March-2023, Available :http://www.ijsdr.org/papers/IJSDR2303017.pdf
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Publication Details: Published Paper ID: IJSDR2303017
Registration ID:204365
Published In: Volume 8 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: 82 - 85
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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