Robust Attack Identification Strategy to Prevent Document Image Forgeries by using Enhanced Learning Methodology-Reference-Cited by-同舟云学术

Robust Attack Identification Strategy to Prevent Document Image Forgeries by using Enhanced Learning Methodology

Published:2023-11-01 Issue: Volume: Page:1-8
ISSN:
Container-title:2023 International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE)
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Author:

Prabu R.T¹,Diwakaran S²,Balaji A³,Prathima Ch⁴,Dhanalakshmi K. M⁵,Vijayakumar S⁶

Affiliation:

1. SIMATS,Saveetha School of Engineering,Department of ECE,Chennai,India

2. Kalasalingam Academy of Research and Education Srivilliputhur,Department of ECE,India

3. Rajalakshmi Institute of Technology,Department of ECE,Chennai,India

4. Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College),Department of Data Science School of Computing,Tirupati,India

5. S.A Engineering College,Department of ECE,Chennai,India

6. Paavai Engineering College,Department of ECE,Namakkal,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10368386/10368609/10369395.pdf?arnumber=10369395

Reference12 articles.

1. Comprehensive analyses of image forgery detection methods from traditional to deep learning approaches: an evaluation

2. Deep Learning Based Forgery Attack on Document Images;Prasanna-Lakshmi;International Journal of Innovative Research in Science, Engineering and Technology,2023

3. Image Forgery Detection Using Open-Cv and Md5;Naidu;Industrial Engineering Journal,2023

4. Document Image Forgery Detection Based on Deep Learning Models

5. Robust Document Image Forgery Localization Against Image Blending

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