Offline Handwritten Signature Analysis for Age Classification using Deep Features-Reference-Cited by-同舟云学术

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Offline Handwritten Signature Analysis for Age Classification using Deep Features

Published:2023-05-26 Issue: Volume: Page:
ISSN:
Container-title:2023 4th International Conference for Emerging Technology (INCET)
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Author:

Kumar Sathish¹,Gornale Shivanand¹,Patil Abhijit²,S Rashmi³

Affiliation:

1. Rani Channamma University,Department of Computer Science,Belagavi,India

2. Gulbarga University,PG Center Halhalli,Department of Computer Science Line 3,Kalaburagi,India

3. West Virginia University,Department of Mechanical and Aerospace Engineering,Morgantown,West Virginia,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10169136/10169900/10170459.pdf?arnumber=10170459

Reference16 articles.

2. Age and gender-invariant features of handwritten signatures for verification systems;abdali,2014

3. Determination Of Writer's Age Using English Handwritten Documents;hiremath,2010

4. Age dependency in handwritten dynamic signature verification systems - ScienceDirect;guest,0

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1. MuBDA: Multimodal Biometric Data Analysis for Gender Classification Using Deep Learning Techniques;Lecture Notes in Networks and Systems;2024

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