A Study on Miao Batik Pattern Design Based on Style Transfer Algorithms

The purpose of this research is to protect and conserve the Miao batik, a form of intangible cultural heritage, and to stimulate the creative evolution of its traditional patterns.It investigates the use of artificial intelligence technologies for the digital preservation and creative redesign of Miao batik patterns. Through the extraction and analysis of pattern elements, alongside the application of convolutional neural networks and style transfer algorithms, the research reimagines the features and aesthetics of these traditional patterns. The findings demonstrate that this approach not only supports the self-renewal and enhancement of the cultural value of Miao batik but also paves the way for its innovative evolution in a contemporary context.

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Publication Details

Published
2024-12-27
DOI
https://doi.org/10.1109/icairc64177.2024.10900223
Citations
1
Primary Topic
Generative Adversarial Networks and Image Synthesis
Type
article
Field-Weighted Citation Impact
0.25
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article

A Study on Miao Batik Pattern Design Based on Style Transfer Algorithms

Lin Liu, Xiaoyun Sun
1 citations
Generative Adversarial Networks and Image Synthesis
0.25
article

A Study on Miao Batik Pattern Design Based on Style Transfer Algorithms

Lin Liu, Xiaoyun Sun
article en
1 citations

Abstract

The purpose of this research is to protect and conserve the Miao batik, a form of intangible cultural heritage, and to stimulate the creative evolution of its traditional patterns.It investigates the use of artificial intelligence technologies for the digital preservation and creative redesign of Miao batik patterns. Through the extraction and analysis of pattern elements, alongside the application of convolutional neural networks and style transfer algorithms, the research reimagines the features and aesthetics of these traditional patterns. The findings demonstrate that this approach not only supports the self-renewal and enhancement of the cultural value of Miao batik but also paves the way for its innovative evolution in a contemporary context.

Hubei University of Technology (CN)
Openalex Percentile: Top 42%
Generative Adversarial Networks and Image Synthesis
0.25
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