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By:
Jie Chen and  Li Zhao  
Open Access
|Oct 2019

Figures & Tables

Figure 1.

Data flow diagram of GAN
Data flow diagram of GAN

Figure 2.

Experimental results
Experimental results

NETWORK STRUCTURE OF THE DISCRIMINATOR

operationConvolution kernel sizepaceConvolution kernel numberBatch normalizationactivation function
convolution4×4264NoLeaky Relu
convolution4×42128YesLeaky Relu
convolution4×42256YesLeaky Relu
convolution4×42512YesLeaky Relu

NETWORK STRUCTURE OF THE GENERATOR

operationConvolution kernel sizepaceConvolution kernel numberBatch normalizationactivation function
convolution7×7132NoRelu
convolution3×3264YesRelu
convolution3×32128YesRelu
convolution3×32128YesRelu
convolution3×32128YesRelu
convolution3×32128YesRelu
convolution3×32128YesRelu
convolution3×32128YesRelu
deconvolution3×31/2128YesRelu
deconvolution3×31/2128YesRelu
deconvolution3×31/2128YesRelu
deconvolution3×31/2128YesRelu
deconvolution3×31/2128YesRelu
deconvolution3×31/264YesRelu
deconvolution3×31/232YesRelu
deconvolution7×713YesRelu
Language: English
Page range: 93 - 98
Published on: Oct 8, 2019
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2019 Jie Chen, Li Zhao, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.