GENERATIVE ADVERSARIAL NETWORK AND DIGITAL ART INTERACTIONS WITH METAVERSE MARKETING

Authors : Kemal Gökhan Nalbant, Sevgi Aydin, Şevval Uyanik

Pages : 375-396

Doi:10.26468/trakyasobed.1301771

View : 120 | Download : 113

Publication Date : 2023-12-29

Article Type : Research Paper

Abstract :The application of machine learning, deep learning, and artificial intelligence is ubiquitous across various domains. The Generative Adversarial Network (GAN) is considered a remarkable deep learning architecture among its peers. Provided that an ample quantity of data samples is fed to the GAN model, it is feasible to generate novel samples of the same data category. By providing the system with a large dataset of cat images, it can acquire the ability to recognize the defining characteristics of a feline and subsequently produce novel cat photos. This architectural design served as the foundation for numerous programs. The domain of digital art has experienced significant impact in recent times. The GAN has emerged as a prominent deep learning framework that has had a significant impact on the field of digital art. This article primarily focuses on elucidating the fundamental aspects of GAN, including its definition, operational mechanism, classification, practical implementations, and correlation with digital art. Simultaneously, inquiries pertaining to the definition of digital art, its practical implementations, and its correlation with the metaverse and digital marketing are being scrutinized.
Keywords : Çekişmeli Üretici Ağ, Dijital Sanat, Yapay Zeka, Metaverse Pazarlama, Dijital Pazarlama

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