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Proceedings Paper

Research on denoising technology of Generative Adversarial Networks (GAN) based on big data
Author(s): Xiancheng Feng; Xinyu Zhang; Wu Qiu
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Paper Abstract

At present, there are more and more urgent demands to realize image/video adaptive enhancement in many different fields. In the case of large data, it is of great practical significance to study how to remove redundant noise from image/video, design a denoising image restoration technology based on large data antagonism generation network, and realize image/video enhancement technology in many fields. This paper mainly studies the further improvement and optimization of GAN, including image denoising oriented GAN model construction, GAN model improvement and training optimization, mobile phone image enhancement based on large data, etc. The experimental results show that GAN network denoising technology has been successfully applied in many image processing applications.

Paper Details

Date Published: 14 February 2020
PDF: 4 pages
Proc. SPIE 11431, MIPPR 2019: Parallel Processing of Images and Optimization Techniques; and Medical Imaging, 1143104 (14 February 2020); doi: 10.1117/12.2538095
Show Author Affiliations
Xiancheng Feng, Wuhan Institute of Technology (China)
Hubei Engineering Research Ctr. of Video Image and HD Projection (China)
Xinyu Zhang, Wuhan Institute of Technology (China)
Hubei Engineering Research Ctr. of Video Image and HD Projection (China)
Wu Qiu, Hubei Yingtong Telecommunication Cable Co., Ltd. (China)


Published in SPIE Proceedings Vol. 11431:
MIPPR 2019: Parallel Processing of Images and Optimization Techniques; and Medical Imaging
Hong Sun; Bruce Hirsch; Chao Cai, Editor(s)

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