CNN vs GAN in image processing: A comparative analysis
Independent researcher, USA.
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2022, 06(01), 097-106.
Article DOI: 10.30574/wjaets.2022.6.1.0070
Publication history:
Received on 07 May 2022; revised on 12 June 2022; accepted on 14 June 2022
Abstract:
This study compares convolutional neural networks (CNNs) with generative adversarial networks (GANs) in image processing. Image classification and recognition features have been revolutionized through CNNs because of their widespread use in image classification tasks. GANs demonstrate high potential for creating realistic synthesized images that prove useful for enhancing images and carrying out creative work. The evaluation focuses on the unique capabilities and difficulties of CNNs and GANs regarding their utilization across medical, security, and entertainment fields. Research shows that CNNs demonstrate superior performance in classification applications, yet GANs lead image generation operations, particularly through projects like image restoration and inpainting tasks. CNNs and GANs work together in image processing because they provide separate abilities to address various real-world image processing needs.
Keywords:
CNN performance; GAN applications; Image generation; Medical imaging; Image classification; Data augmentation
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Copyright © 2022 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0