GAN in digital image processing

Yan Liu

doi:10.1117/12.2641663

10 November 2022 GAN in digital image processing

Yan Liu

Proceedings Volume 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022); 123483S (2022) https://doi.org/10.1117/12.2641663
Event: 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 2022, Zhuhai, China

Abstract

A generative adversarial network (GAN) is a critical invention in machine learning, and this network has made great progress recently. From the overcoming of target classification to the unification of target detection and segmentation, the fortresses of deep learning have been conquered one after another during the great development of all kinds of GANs. GAN is a class of deep learning frameworks constructed by two neural networks, which have two models named generator and discriminator. The two models learn anything by playing games with each other to produce convincing output. Machine learning practitioners are increasingly turning to the power of GANs for digital image processing, and the applications that benefit from using GANs include generating art and photos from text-based descriptions, upscaling images, transferring images across domains, and many others. Thus it is meaningful to do review research on the representative enhanced GAN architectures that have been devised with their unique features for solving specific digital image processing problems. In this paper, we will review the revolution of GANs and the improvement in digital image processing.

Citation Download Citation

Yan Liu "GAN in digital image processing", Proc. SPIE 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 123483S (10 November 2022); https://doi.org/10.1117/12.2641663

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