• K. Sarada
• B. Naga Sudheer
• P. Radha Madhavi

Abstract: The rise of Machine Learning and Deep Learning has provided organizations with the ability to save time, money, and labor via automated visual content editing. Generative adversarial networks (GANs) can restore photos that have been deleted, as well as replicate missing pieces, which means software that is used to modify photos can't do these tasks. GANs may create pictures from scratch or as part of a content development process where you specify a semantic input. Semantic pictures may be used to provide training data for visual recognition algorithms and to create synthetic training data for forensic recognition in criminal identification.

Indexed Terms: generative adversarial networks (GANs), deep learning, artificial intelligence, image translation.

"PHOTOS TO IMAGE TRANSLATION USING GANS: A REVIEW ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.e793-e796, June-2021, Available :http://www.jetir.org/papers/JETIR2106675.pdf

"PHOTOS TO IMAGE TRANSLATION USING GANS: A REVIEW ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppe793-e796, June-2021, Available at : http://www.jetir.org/papers/JETIR2106675.pdf