Academic Journal of Computing & Information Science, 2024, 7(12); doi: 10.25236/AJCIS.2024.071207.
Zhuoyang Li
School of Statistics and Data Science, Qufu Normal University, Jining, China
This paper explores the growing use of AI-generated images for fraud and the spread of piracy, while AI generated images are widely used in various fields. By using principal component analysis (PCA) to reduce feature dimension, shallow learning methods such as Logistics regression, discriminant analysis, SVM (support vector machine), random forest, KNN (K-nearest neighbor), and deep learning methods with attention mechanism such as Alexnet, Googlenet and Mobilenet are adopted. The AI-generated picture is effectively distinguished from the real picture. The results show that SVM model and Alexnet model show the strongest comprehensive performance in identifying AI-generated images, providing new ideas and methods for solving problems caused by AI-generated images.
Principal component analysis, deep learning, Alexnet, Mobilenet, Pros and Cons Solution distance method (TOPSIS)
Zhuoyang Li. Research on Optimization of AI Image Recognition Performance Based on Multiple Machine Learning Algorithms and Deep Learning Models. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 12: 51-58. https://doi.org/10.25236/AJCIS.2024.071207.
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