Research on Pattern Elements and Colors inApparel Design through Fractal Theory


Dan Li, Chengjun Yuan, Journal of Information Processing Systems Vol. 20, No. 3, pp. 409-417, Jun. 2024  

https://doi.org/10.3745/JIPS.02.0215
Keywords: Apparel Design, Color, fractal theory, pattern
Fulltext:

Abstract

Excellent apparel design can increase market competitiveness. This article briefly introduced the theory of fractals and its application in the field of apparel design. The convolutional neural network (CNN) algorithm was used to assist in the evaluation of apparel designs. In the case analysis, the accuracy of the evaluation was validated by comparing the CNN algorithm with two other intelligent algorithms, support vector machine (SVM) and back propagation (BP). The evaluation of the proposed design showed that compared with SVM and BP algorithms, the CNN algorithm had higher accuracy in evaluating apparel designs. The evaluation result of the proposed apparel design not only further verifies the effectiveness of the CNN algorithm, but also demonstrates that the theory of fractals can be effectively applied in apparel design to provide more innovative designs.


Statistics
Show / Hide Statistics

Statistics (Past 3 Years)
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, D. & Yuan, C. (2024). Research on Pattern Elements and Colors inApparel Design through Fractal Theory. Journal of Information Processing Systems, 20(3), 409-417. DOI: 10.3745/JIPS.02.0215.

[IEEE Style]
D. Li and C. Yuan, "Research on Pattern Elements and Colors inApparel Design through Fractal Theory," Journal of Information Processing Systems, vol. 20, no. 3, pp. 409-417, 2024. DOI: 10.3745/JIPS.02.0215.

[ACM Style]
Dan Li and Chengjun Yuan. 2024. Research on Pattern Elements and Colors inApparel Design through Fractal Theory. Journal of Information Processing Systems, 20, 3, (2024), 409-417. DOI: 10.3745/JIPS.02.0215.