Generative Adversarial Networks: A Comprehensive Review
对抗制
生成语法
计算机科学
人工智能
作者
Pavani Kotha,Venkatesh Babu,Sreejyothsna Ankam
出处
期刊:Lecture notes in networks and systems日期:2024-01-01卷期号:: 105-114
标识
DOI:10.1007/978-981-99-9704-6_9
摘要
Numerous models in the deep learning field have been created as a result of the rise in processing capacity. A generative model called Generative Adversarial Networks (GAN) first appeared in 2014. Many architectures of GAN have been proposed in the process of research conducted on GAN. Any GAN architecture is the result of the competition between two networks, the Generator and Discriminator, to determine the distribution of the sampled data. This process helps in many applications like text to image conversion, style transfer, generating new images, attribute transfer, photo enhancement. This paper helps in knowing about the main working principle of any GAN architecture, recent advances, and applications of GAN.