纺织工程学报2025，Vol.3Issue(2)：65-74,10.
基于深度神经网络的蜡染图像鉴别模型研究
Research on batik image identification model based on deep neural network
摘要
Abstract
In order to inherit the batik technique and academic research,and to improve the accuracy of batik im-age categorization,a batik image identification model based on the combination of Inception V3 deep neural net-work was established by combining Indonesian batik images.In order to solve the problem of the small number of samples in the dataset,the dataset is expanded by using the method of style migration.For the Inception V3 network,the accuracy of the expanded dataset is improved by 9.56%compared with the unexpanded dataset;training the model on the expanded dataset,the accuracy of Inception V3 is 95.1%,VGG16 is 76.1%,and ResNet50 is 91.07%,and the accuracy and recall of each category of the Inception V3 model are higher than the other two alternative models.关键词
深度学习/蜡染图像/风格迁移/图像鉴别/精确率/召回率Key words
deep learning/batik image/style transferring/image identification/precision/recall rate分类
轻工纺织引用本文复制引用
唐文豪,罗维平,杜焱铭,余中祈,张亚鹏..基于深度神经网络的蜡染图像鉴别模型研究[J].纺织工程学报,2025,3(2):65-74,10.基金项目
国家自然科学基金(62103309) （62103309）
湖北省数字化纺织装备重点实验室开放课题(DTL2022001). （DTL2022001）
