Generating Synthetic Images Using Generative Adversarial Network

Generating Synthetic Images Using Generative Adversarial Network
Author(s):
Savani Sachin Dhene, Pranjal Bhosale, Mrunal Avhad, Jay Rawal, Rupali Dalvi
Keywords:
Adversarial, Artificial Intelligence, Criminal, Deep learning, Face generation, Generative, GAN, NLP.
Abstract
Text to image technology with generative[3] adversarial networks (GAN) is a deep learning model technology. For many years due to lack of knowledge of technological resources the police department has to call the sketch artist to get the face of the criminal.The traditional method takes lots of time hence proposed approach uses text as an input of human facial traits and gives almost a similar image of criminal.Artificial intelligence (AI) has a challenge with converting information between text and image (NLP) that links natural language processing and image processing. As a result, we present a new efficient system based on the generative adversarial network (GAN) that will enhance performance by simple procedures. Our work primarily focuses on criminal face generation with minimum time consumption that extracts face traits from text descriptions and creates a realistic human face.
Article Details
Unique Paper ID: 158176 Publication Volume & Issue: Volume 9, Issue 9 Page(s): 30 - 32
Article Preview & Download

Share This Article

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org