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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM28467

AI Generated Image Detection Tool

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM28467

Volume:

8 |

2 |

Feb 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SD

Shivam Durgude

SP

Swarali Patil

PP

Priyanka Pawar

NS

Neha Shinde

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Abstract

In the era of rapidly advancing artificial intelligence, there is a growing need for a reliable and efficient tool to discern between human-generated and AI-generated images. Existing methods often lack accuracy and real-time processing capabilities, hindering their applicability in various domains. This project addresses the challenge of developing a robust image analysis tool using advanced neural networks to accurately identify whether an image is AI-generated or created by human hands. Our approach involves leveraging the power of deep learning techniques, specifically Convolutional Neural Networks (CNNs), to analyze images and determine whether they are AI-generated or not. The process encompasses several essential steps, including data preprocessing, neural network architecture selection, model training, and rigorous evaluation. Through this project, we aim to contribute to the field of image analysis by providing a robust tool for detecting AI-generated images. Key aspects of our methodology include data preparation, CNN implementation, and rigorous validation techniques, ensuring the tool’s accuracy and reliability.

KEYWORDS

Convolutional Neural Networks AI-generated Images

Cite This Article

Shivam Durgude, Swarali Patil, Priyanka Pawar, Neha Shinde, "AI Generated Image Detection Tool," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 2, Feb 2024.

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Publication Date

12/31/45324

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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