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Bimonthly Since 1986 |
ISSN 1004-9037
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Publication Details |
Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
Distributed by:
China: All Local Post Offices
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Abstract
Computer vision is the field of artificial intelligence (AI) used in industrial applications. Text-to-image creation with Generative Adversarial Networks (GAN) is a deep learning model which can provide images from text descriptions. This project proposes the development of a text-to image synthesis system using Generative Adversarial Networks (GANs). The GAN architecture will be utilized to generate high-quality images from text descriptions. The system will be trained on a dataset of text descriptions and paired images. It will be evaluated on the quality of the generated images and the accuracy in capturing the semantic information from the text descriptions. The results will be compared against existing text-to-image synthesis systems. This project will provide a useful tool for researchers in the field of computer vision and natural language processing. Keywords— Artificial Intelligence, GAN(Generative Adversarial Networks) .
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