Combining Artificial Intelligence Algorithms to Optimize the Digital Innovation Design of Dong Brocade Patterns Research

AI technology in the development and application of traditional texture recovery and reproduction, deep learning models for traditional texture information and color information consistency migration is still deficient, this paper by using the visual Transformer network advantage and visual Transformer network Transformer encoder structure optimization.That is to say, in the Transformer encoder, the multi-head self-attention module and feed-forward network module are called to process the input data and extract the image features, and then join the edge preservation smoothing technology to remove the strong edge information, preserve some weak edges and local colors, and generate the image texture information with the input texture.The color interpolation method is used to achieve the consistency of texture color texture and image texture migration.The result images of Dong brocade texture style migration show that the image texture migration model based on visual transformer is more capable of generating images with the best style loss value and the best content loss value, and is able to obtain more than 70% of user preference.

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-04-20
DOI
https://doi.org/10.61091/jcmcc127b-347
Citations
1
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
2.45
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Combining Artificial Intelligence Algorithms to Optimize the Digital Innovation Design of Dong Brocade Patterns Research

1 citations
Journal of Combinatorial Mathematics and Combinatorial Computing
E-commerce and Technology Innovations
2.45
article

Combining Artificial Intelligence Algorithms to Optimize the Digital Innovation Design of Dong Brocade Patterns Research

article en
1 citations

Abstract

AI technology in the development and application of traditional texture recovery and reproduction, deep learning models for traditional texture information and color information consistency migration is still deficient, this paper by using the visual Transformer network advantage and visual Transformer network Transformer encoder structure optimization.That is to say, in the Transformer encoder, the multi-head self-attention module and feed-forward network module are called to process the input data and extract the image features, and then join the edge preservation smoothing technology to remove the strong edge information, preserve some weak edges and local colors, and generate the image texture information with the input texture.The color interpolation method is used to achieve the consistency of texture color texture and image texture migration.The result images of Dong brocade texture style migration show that the image texture migration model based on visual transformer is more capable of generating images with the best style loss value and the best content loss value, and is able to obtain more than 70% of user preference.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127b
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
E-commerce and Technology Innovations
2.45
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.