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Improved Deep Neural Network for Cross-Media Visual Communication

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成果类型:
期刊论文
作者:
Miao, Yubo
通讯作者:
Miao, Yubo(t20100701@csuft.edu.cn)
作者机构:
[Miao, Yubo] Cent South Univ Forestry & Technol, Coll Furniture & Art Design, Changsha 410000, Hunan, Peoples R China.
通讯机构:
[Miao, Y.] C
College of Furniture and Art Design, Central South University of Forestry and Technology, Hunan, Changsha, China
语种:
英文
期刊:
Computational Intelligence and Neuroscience
ISSN:
1687-5265
年:
2022
卷:
2022
机构署名:
本校为第一机构
院系归属:
家具与艺术设计学院
摘要:
Cross-media visual communication is an extremely complex task. In order to solve the problem of segmentation of visual foreground and background, improve the accuracy of visual communication scene reconstruction, and complete the task of visual real-time communication. We propose an improved generative adversarial network. We take the generative adversarial network as the basis and add a combined codec package to the generator, while configuring the generator and discriminator as a cascade structure, preserving the feature upsampling and downsa...

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