The role of iconography in shaping Chinese national identity: Analyzing its representation in visual media and political propaganda

Abstract

The creation of cultural iconography that may reflect national culture and encourage individuals to identify with Chinese culture has always been a difficult issue. In this study, we present a symbolic creation framework for Chinese national cultural identity constructed from visual pictures using generative adversarial networks (GAN). To enhance the structure collapse phenomena of generative adversarial systems, form search regular procedure and generator cross-loss factors on the basis of GAN should be combined. To enhance the real-time efficiency of the model by lowering the parameters in the model, the conventional convolutional component of the generator in the system’s architecture is substituted with a significant recoverable convolution. The notions of iconography and character as they relate to symbols are discussed in this essay.  It also advises using iconography as a technique of symbolic imagery to give emergent symbols identity.  The design in this study may create significant performance ethnic cultural symbols while preserving superior temporal performance, according to the findings of rigorous testing on real datasets, which may have practical application value. The accuracy, precision, recall, and F1 of the system in this study are 91.54%, 89.02%, 90.96%, and 87.48%.