Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 10, Issue 1


Published
on

March 21, 2025


Pages


DOI

Article

Deep Learning Modeling and Visual Aesthetics Integration Path in Cultural and Creative Designs

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Authors

Hailong Shen Affiliation:
School of Art and Design, Suzhou Chien-Shiung Institute of Technology, Taicang, Jiangsu, 215411, China.
and Qingguo Sun Affiliation:
School of Art and Design, Suzhou Chien-Shiung Institute of Technology, Taicang, Jiangsu, 215411, China.


Abstract

As an emerging industry with a wide range of prospects and great potential, cultural creative design is receiving attention and research from many scholars. As the first element affecting human vision, color is particularly important in the process of cultural product design and artistic creation. The article proposes an adaptive extraction model for image primary color based on the contour coefficient method and an intelligent color matching algorithm that integrates visual aesthetics. Through experiments, it is found that in the color aesthetics calculation experiments, the color aesthetics of each color scheme is in line with the aesthetics principle, in which the highest color aesthetics values of Scheme 1 and Scheme 5 are 1.24 and 1.03, respectively. From this, it can be concluded that the color matching algorithm proposed in this paper has a good role in the design of cultural and creative products.


Keywords

Adaptive primary color extraction, Color matching, Deep learning model, Cultural creative design, 68T07


Citation

Shen, H. & Sun, Q. (2025). Deep learning modeling and visual aesthetics integration path in cultural and creative designs. Applied Mathematics and Nonlinear Sciences, 10(1). https://doi.org/10.2478/amns-2025-0649

Published by: Engineering Journals

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