Source of Publication
SpringerBriefs in Computer Science
This chapter explores the practical applications of GANs in the real world. As previously discussed, GANs are deep neural networks capable of generating new data resembling a target distribution, such as images and audio signals. GANs have garnered much attention in machine learning in recent years due to their versatile usage across various industries. This chapter will delve into the various ways in which GANs have been employed in real-world applications. They include but are not limited to the generation of synthetic data for training machine learning models, the creation of photorealistic images and videos, the generation of human faces, the production of fake videos, image-to-image translation, text-to-image translation, CycleGAN, enhancement of image resolution, semantic image inpainting, and text-to-speech. A comprehensive overview of the exciting possibilities of GANs and their impact on various industries will be provided. By the end of the chapter, the reader will clearly understand the practical applications of GANs and their potential to shape the future.
Springer International Publishing
CycleGAN, Data collection, Data preparation, Deep fake, Face generation, GANs applications, Hyperparameter tuning, Image enhancement, Image-to-image translation, Semantic image inpainting, Text to image, Training
Kaddoura, Sanaa, "Real-World Applications" (2023). All Works. 5913.
Indexed in Scopus