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<div><p>Harnessing the power of artificial intelligence(AI) approaches to innovatively generating the vector graphics of fine-grained patterns has become an important task in image edge extraction, particularly on the domain of intangible cultural heritage (ICH) images where they are typ...

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Bibliographic Details
Main Author:	Anqi Chen (1950547) (author)
Other Authors:	Yicui Peng (21526573) (author), Meng Li (79487) (author), Hao Chen (5190) (author), Chang Liu (35901) (author), Jinrong Hu (5800001) (author), Xiang Wen (6563624) (author), Guo Huang (2388922) (author)
Published:	2025
Subjects:	Science Policy Plant Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> harnessing reliable practical reference proposed method provides pattern recognition techniques machine learning algorithms intangible cultural heritage experimental results show convolutional neural networks reduce image noise xception algorithm based two different types generate vector graphics dimensional vectorial images grained pattern based qiang embroidery patterns image edge extraction vector graphics qiang embroidery image processing image information edge extraction edge detection shape characteristics processing methods local mean innovatively generating important task higher autonomy grained patterns example due concept contained complex edges clearly identified artistic reinterpretation artificial intelligence accurately extract
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