Harnessing Machine Learning for Discerning AI-Generated Synthetic Images

project
Jan 2023

This study focuses on employing machine learning techniques, including advanced deep learning models like ResNet, VGGNet, DenseNet, and a baseline SVM and custom CNN, to discern between AI-generated and genuine images. The research uses the CIFAKE dataset and aims to advance the field of digital media integrity.

  • The paper discusses using machine learning models to identify AI-generated synthetic images. It compares the performance of various models including ResNet, VGGNet, DenseNet, SVM, and CNN on the CIFAKE dataset. The study contributes to understanding the effectiveness of these models in distinguishing between real and AI-generated images, emphasizing the importance of accurate classification in the era of digital misinformation.

    • Paper

    • Machine Learning
    • AI-Generated Images
    • Deep Learning
    • ResNet
    • VGGNet
    • + more
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