现代信息科技2025，Vol.9Issue(2)：24-32,9.DOI:10.19850/j.cnki.2096-4706.2025.02.005
面向小样本苗绣图像的生成与识别研究
Research on Generation and Recognition of Few-Shot Miao Embroidery Images
摘要
Abstract
To address the issues of insufficient sample sizes and low recognition accuracy of Miao embroidery images,this paper proposes a novel Miao embroidery image classification model,which combines StyleGAN2 with optimized ResNet50 by the Efficient Channel Attention(ECA).Firstly,StyleGAN2 is utilized to train and generate on the original Miao embroidery dataset,thereby augmenting the Few-Shot dataset.Subsequently,the ECA Attention Mechanism is integrated into the ResNet50 backbone network to enhance the feature extraction capability of the model.Ultimately,the new StyleGAN2-ECA-ResNet50 model is created by combining StyleGAN2 and ResNet50 optimized by ECA for the recognition of Few-Shot Miao embroidery images.Experimental results show that the accuracy of this method reaches 89.29%on the test set,which is an improvement of 5.87%over the traditional ResNet50 model and surpasses several advanced Deep Learning models in performance.关键词
苗绣/小样本图像分类/数据增强/StyleGAN2/ECAKey words
Miao embroidery/Few-Shot image classification/data augmentation/StyleGAN2/ECA分类
信息技术与安全科学引用本文复制引用
吴菁,杨邦勤,张银建,李明珠,陈妍..面向小样本苗绣图像的生成与识别研究[J].现代信息科技,2025,9(2):24-32,9.基金项目
贵州省科技计划项目(黔科合基础-ZK[2021]一般340) （黔科合基础-ZK[2021]一般340）
贵州省教育厅自然科学研究项目(黔教技[2023]061号) （黔教技[2023]061号）
贵州省教育厅自然科学研究项目(黔教技[2023]012号) （黔教技[2023]012号）
贵州省教育厅自然科学研究项目(黔教技[2022]047号) （黔教技[2022]047号）
贵州民族大学博士科研启动项目(GZMUZK[2024]QD11) （GZMUZK[2024]QD11）
