Generative Fusion: AI-Powered Image Synthesis Through Gan and NLP Integration

Generative Fusion: AI-Powered Image Synthesis Through Gan and NLP Integration

                   P KARTHIK                                                 P SOHAIL KHAN                                         N DINIESH CHAITANYA

Students Соmрuter Sсienсe and                         Students Computer Science and                   Students Computer Science and

Engineering  Dr.Mgr Educational                     Engineering Dr.Mgr Educational                  Engineering Dr.Mgr Educational

  Research Institute University,                             Research Institute University ,                         Research Institute University ,

           Chennai,India                                                         Chennai,India                                                    Chennai,India

          COORDINATOR

           DR.REKHA.K.K                                                                                                                      C.SUBBULAKSHMI

     DR.A.VINOTH KUMAR                                                                                                      ASSOCIATE PROFESSOR

   ASSOCIATE PROFESSORS                                                                                            DR.MGR EDUCATIONAL AND

   DR.MGR EDUCATONAL AND                                                                                  RESEARCH INSTITUTE UNIVERSITY

RESEARCH INSTITUTE UNIVERSITY

ABSTRACT

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.