№1, 2022


Yadigar N. Imamverdiyev, Firangiz I. Musayeva

Recently, a lot of research has been done on the use of generative models in the field of computer vision and image classification. At the same time, effective work has been done with the help of an environment called generative adversarial networks, such as video generation, music generation, image synthesis, text-to-image conversion. Generative adversarial networks are artificial intelligence algorithms designed to solve the problems of generative models. The purpose of the generative model is to study the set of training patterns and their probable distribution. The article discusses generative adversarial networks, their types, problems, and advantages, as well as classification and regression, segmentation of medical images, music generation, best description capabilities, text image conversion, video generation, etc. general information is given. In addition, comparisons were made between the generative adversarial network algorithms analyzed on some criteria (pp.20-27).

Keywords: Neural networks, Generative models, Generative adversarial networks, Auto encoders, Generator, Discriminator
DOI : 10.25045/jpit.v13.i1.03

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