skip to main content

A Novel CNN Model for Classification of Chinese Historical Calligraphy Styles in Regular Script Font

Sensors (Basel, Switzerland), 2023-12, Vol.24 (1), p.197 [Tạp chí có phản biện]

COPYRIGHT 2023 MDPI AG ;2023 by the authors. 2023 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s24010197 ;PMID: 38203059

Tài liệu số/Tài liệu điện tử

Trích dẫn Trích dẫn bởi
  • Nhan đề:
    A Novel CNN Model for Classification of Chinese Historical Calligraphy Styles in Regular Script Font
  • Tác giả: Huang, Qing ; Li, Michael ; Agustin, Dan ; Li, Lily ; Jha, Meena
  • Chủ đề: Analysis ; Calligraphy, Chinese ; Chinese calligraphy ; convolutional neural network (CNN) ; deep learning ; handwriting recognition ; Neural networks ; styles classification
  • Là 1 phần của: Sensors (Basel, Switzerland), 2023-12, Vol.24 (1), p.197
  • Mô tả: Chinese calligraphy, revered globally for its therapeutic and mindfulness benefits, encompasses styles such as regular (Kai Shu), running (Xing Shu), official (Li Shu), and cursive (Cao Shu) scripts. Beginners often start with the regular script, advancing to more intricate styles like cursive. Each style, marked by unique historical calligraphy contributions, requires learners to discern distinct nuances. The integration of AI in calligraphy analysis, collection, recognition, and classification is pivotal. This study introduces an innovative convolutional neural network (CNN) architecture, pioneering the application of CNN in the classification of Chinese calligraphy. Focusing on the four principal calligraphy styles from the Tang dynasty (690-907 A.D.), this research spotlights the era when the traditional regular script font (Kai Shu) was refined. A comprehensive dataset of 8282 samples from these calligraphers, representing the zenith of regular style, was compiled for CNN training and testing. The model distinguishes personal styles for classification, showing superior performance over existing networks. Achieving 89.5-96.2% accuracy in calligraphy classification, our approach underscores the significance of CNN in the categorization of both font and artistic styles. This research paves the way for advanced studies in Chinese calligraphy and its cultural implications.
  • Nơi xuất bản: Switzerland: MDPI AG
  • Ngôn ngữ: English
  • Số nhận dạng: ISSN: 1424-8220
    EISSN: 1424-8220
    DOI: 10.3390/s24010197
    PMID: 38203059
  • Nguồn: PubMed Central (Open access)
    DOAJ Directory of Open Access Journals
    Geneva Foundation Free Medical Journals at publisher websites
    ROAD: Directory of Open Access Scholarly Resources
    ProQuest Central

Đang tìm Cơ sở dữ liệu bên ngoài...