A Visual Communication Design Study: Graphic Element Design Under Traditional Handwork


Gengming Li, Journal of Information Processing Systems Vol. 19, No. 2, pp. 203-210, Apr. 2023  

https://doi.org/10.3745/JIPS.02.0192
Keywords: Convolutional Neural Network, Graphic Elements, Traditional Handwork, visual communication
Fulltext:

Abstract

The addition of traditional elements can enhance the uniqueness of visual communication design. This paper briefly introduced visual communication and applications of traditional elements in visual communication design and applied paper cuts, a handmade graphic element, to the logo design of Dezhou University's 50th anniversary. The convolutional neural network (CNN) algorithm and the analytic hierarchy process method were applied to evaluation analysis and compared with the support vector machine (SVM) algorithm. The results of the CNN algorithm on the test set verified its effectiveness. The evaluation results of the CNN algorithm were similar to the manual evaluation results, further proving the effectiveness and high efficiency of the CNN algorithm. The hierarchical analysis and the analysis of the assessment results of the CNN algorithm found that the two logo designs made full use of paper cuts.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from November 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.




Cite this article
[APA Style]
Li, G. (2023). A Visual Communication Design Study: Graphic Element Design Under Traditional Handwork. Journal of Information Processing Systems, 19(2), 203-210. DOI: 10.3745/JIPS.02.0192.

[IEEE Style]
G. Li, "A Visual Communication Design Study: Graphic Element Design Under Traditional Handwork," Journal of Information Processing Systems, vol. 19, no. 2, pp. 203-210, 2023. DOI: 10.3745/JIPS.02.0192.

[ACM Style]
Gengming Li. 2023. A Visual Communication Design Study: Graphic Element Design Under Traditional Handwork. Journal of Information Processing Systems, 19, 2, (2023), 203-210. DOI: 10.3745/JIPS.02.0192.