Generative adversarial networks (GANs): Introduction, Taxonomy, Variants, Limitations, and Applications

• Published in: Multimedia tools and applications Vol. 83; no. 41; pp. 88811 - 88858
• Main Authors: Sharma, Preeti, Kumar, Manoj, Sharma, Hitesh Kumar, Biju, Soly Mathew
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.12.2024; Springer Nature B.V
• Subjects: Computer Communication Networks; Computer Science; Data Structures and Information Theory; Deep learning; Deepfake; Demand analysis; Effectiveness; Forensic sciences; Generative adversarial networks; Multimedia; Multimedia Information Systems; Neural networks; Special Purpose and Application-Based Systems; Taxonomy; Visual fields; Deep learning; Image vision; Deep fakes; GAN variants; GAN architecture; Digital forensics; Generative adversarial network; GAN models; Deep learning based methods

The growing demand for applications based on Generative Adversarial Networks (GANs) has prompted substantial study and analysis in a variety of fields. GAN models have applications in NLP, architectural design, text-to-image, image-to-image, 3D object production, audio-to-image, and prediction. This...