基于深度学习的汉字书法风格自动识别与分类研究  

Research on Automatic Recognition and Classification of Chinese Calligraphy Styles Based on Deep Learning

作　　者：李涛[1] 苑颖[1] 付亚超 LI Tao;YUAN Ying;FU Yachao(Yinchuan University of Energy,Yinchuan Ningxia 750100,China)

机构地区：[1]银川能源学院,宁夏银川750100

出　　处：《信息与电脑》2024年第20期185-187,共3页Information & Computer

基　　金：宁夏回族自治区教育厅高等学校科学研究项目(项目编号:NYG2024269)。

摘　　要：本文聚焦于深度学习在汉字书法风格识别与分类的应用,通过文献分析,明确了研究问题,并筛选了高价值论文,同时采用构建深信度网络方法精准切割书法作品,提取单个书法字,再利用深信度网络进行风格识别与分类。实验结果表明,该方法能有效识别与分类汉字书法风格。This paper focuses on the application of deep learning in the recognition and classification of Chinese calligraphy styles.Through literature analysis,the research problem is clarified and high-value papers are screened,while the method of constructing a deep confidence network is used to accurately cut the calligraphic works,extract the individual calligraphic characters,and then use the deep confidence network to recognize and classify the styles.The experimental results show that the method can effectively recognize and classify the calligraphy style of Chinese characters.

关 键 词：深度学习 汉字书法 自动识别 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]