风格(视觉艺术)
计算机科学
算法设计
算法
历史
考古
标识
DOI:10.1109/icid64166.2024.11024662
摘要
The continuous development of artificial intelligence technology is driving the transformation of traditional cultural techniques, leading the cultural industry into the digital age. Addressing the current issues of limited innovation in Qiang embroidery patterns and constrained automatic generation, this paper proposes a style transfer algorithm based on pre-trained convolutional neural networks for Qiang embroidery patterns. This algorithm aims to preserve the traditional artistic characteristics of Qiang embroidery to the fullest extent while achieving rapid and accurate style transfer. Firstly, research and compilation of Qiang embroidery patterns are conducted, and the patterns are extracted. These patterns are then inputted into the style transfer algorithm, and parameters and iteration schemes are adjusted to transfer the style of Qiang embroidery onto the content image, resulting in innovative design schemes for Qiang embroidery patterns that are also applied to cultural and creative products. The results demonstrate the self-renewal of traditional patterns and illustrate the feasibility of intelligent-assisted cultural and creative design, thereby enhancing the cultural value of Qiang embroidery cultural and creative products.
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