Application of blue and white image style transfer in ceramic products
Yu Nie, Linyun Luo, Yuewen Xiang, Yilai Zhang, Yongkang Peng, Chenyang Liao, Guanghua Song
Jingdezhen Ceramic Institute Jiangxi Vocational and Technical College of Information Application
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摘要与影响
The rapid development of artificial intelligence technology and deep learning technology has also promoted the popularization and application of image style transfer in all walks of life. In the traditional ceramic industry, the application of image style transfer technology is still rare. This article is based on the style transfer training of ceramic blue and white images and uses three methods of rapid style transfer, direct style transfer and image pre-processing style transfer to conduct experiments. According to the results of image quality evaluation, it is concluded that the method suitable for the style transfer of ceramic blue and white images is the image pre-processing style transfer method.
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计算机 / AIGenerative Adversarial Networks and Image Synthesis
Advanced Neural Network Applications · Digital Media and Visual Art
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