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@article{158176,
        author = {Savani Sachin Dhene and Pranjal Bhosale and Mrunal Avhad and Jay Rawal and Rupali Dalvi},
        title = {Generating Synthetic Images Using Generative Adversarial Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {9},
        pages = {30-32},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=158176},
        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.},
        keywords = {Adversarial, Artificial Intelligence, Criminal,  Deep learning, Face generation, Generative, GAN, NLP.},
        month = {},
        }