Abstract
With the development of technology, graphic design tools are becoming more and more perfect, which allows graphic designers to realize their dream designs, achieve more special effects, and thus expand their conceptual choices. The application of various new technologies in graphic design can promote the development of the graphic design industry. The emergence of artificial intelligence (AI) has broken through the layout design in traditional graphic design. In this article, the author proposes the creation of a graphic design assistant system based on AI drawing on the deep learning (DL) theory. According to the DL theory, the image is segmented by the class variance. The voxelized image matrix of a two-dimensional (2D) model is input into a convolution-automatic encoder (CAE) as input data. The input data first pass through the convolution layer of the CAE, which mainly completes the mapping of features. The research results show that the average aesthetic evaluation of the system design works in this study is higher than that of CAD software and PS software, and the total average score is as high as 8.788, which shows that the system design works in this study are more in line with the requirements of professional understanding.
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