Doc-Sheild Plagiarism Detection Improving Accuracy and Efficiency Enhancement in Text and Image Similarity Detection

T. Sri Harsha; P. Shivani | K. Aashritha | P. Akshay; Mrs. Pethota Swaroopa

Title:
Doc-Sheild Plagiarism Detection Improving Accuracy and Efficiency Enhancement in Text and Image Similarity Detection

Authors:
Mrs. Pethota Swaroopa | T. Sri Harsha | P. Shivani | K. Aashritha | P. Akshay

Cite This Article :

Mrs. Pethota Swaroopa | T. Sri Harsha | P. Shivani | K. Aashritha | P. Akshay "Doc-Sheild Plagiarism Detection Improving Accuracy and Efficiency Enhancement in Text and Image Similarity Detection" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-9 | Issue-1, February 2025, pp.651-652, URL: https://www.ijtsrd.com/papers/ijtsrd73834.pdf

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Abstract :
Plagiarism in both the academic and professional world attacks the integrity of the intellect and stifles innovation. Traditional plagiarism detection systems can adequately identify text duplication but may lack the efficiency of detecting paraphrased, translated, or contextual variations of text content as well as plagiarized graphical elements, including flowcharts. This paper will outline a complete system that uses a combination of Artificial Neural Networks (ANNs), Natural Language Processing (NLP), and deep learning techniques for both textual and visual plagiarism. It has proved to be much more accurate in terms of plagiarism detection, especially with an 81.91% success rate for flowchart plagiarism, providing an efficiency gain for semantic similarity detection, establishing a new standard for academic integrity tools.

Keywords :
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Publication Details:

Unique Identification Number : IJTSRD73834

Published In : Volume-9 | Issue-1, February 2025

Page Number(s) : 651-652

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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