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Analysis of the performance of deep learning algorithms in image recognition

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DOI: 10.23977/jipta.2024.070102 | Downloads: 25 | Views: 223

Author(s)

Kaile Sun 1

Affiliation(s)

1 Zhengzhou Business University, Zhengzhou, 451200, China

Corresponding Author

Kaile Sun

ABSTRACT

This paper delves into the application and performance of deep learning algorithms in the field of image recognition. By comparing different deep learning models such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Generative Adversarial Networks (GAN), we analyze the efficiency and accuracy of these models in handling various image recognition tasks. The research also includes discussions on optimization strategies for these algorithms and potential challenges and solutions in real-world applications. 

KEYWORDS

Deep learning, image recognition, Convolutional Neural Network, Recurrent Neural Network, Generative Adversarial Network, performance analysis

CITE THIS PAPER

Kaile Sun, Analysis of the performance of deep learning algorithms in image recognition. Journal of Image Processing Theory and Applications (2024) Vol. 7: 12-18. DOI: http://dx.doi.org/10.23977/jipta.2024.070102.

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