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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM28467
Volume:
8 |
2 |
Feb 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
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.
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
Publication Date
12/31/45324
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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