Year: 2025
Type: article
Abstract: The real world which is working with artificial intelligence generates different kinds of algorithms which are helping us in solving the realistic problems and generating images using natural language processing(NLP) which helps in building a communication with computer and human. Now in the present generation generating images with verbal descriptions has gained much popularity. The generative adversarial network (GAN) which belongs to deep learning family model helps us in generating the image by the conjunction with AIML(Artificial Markup Language)which helps the users in generating better graphics directly with the user input instructions. In general there are two main parts required for text to image synthesis with GANs: 1. Discriminator 2. Generator The working of generator is it should take the input provided by the user and generate the realistic image. It takes the text as input and gives image as output. The job of discriminator is like a gatekeep who always stops the fake one to not let enter as output.
DOI: 10.55041/ijsrem44258
Authors: P KARTHIK, N DINIESH
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409391256