Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (17): 29-36.DOI: 10.3778/j.issn.1002-8331.2103-0297

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Chinese Character Generation Method Based on Deep Learning

HUANG Zijun, CHEN Qi, LUO Wenbing   

  1. 1.School of Mathematics and Information Science, Nanchang Normal University, Nanchang 330022, China
    2.School of Computer Information Engineering, Jiangxi Normal University, Nanchang 330022, China
  • Online:2021-09-01 Published:2021-08-30



  1. 1.南昌师范学院 数学与信息科学学院,南昌 330022
    2.江西师范大学 计算机信息工程学院,南昌 330022


Handwritten Chinese Character Generation(HCCG) is an important research direction in machine learning. In the past two decades the studies of handwritten Chinese character generation can be roughly divided into two stages:the research in the early stage mainly used the explicit characteristics of Chinese characters, such as the structure and strokes, to realize the decomposition of Chinese characters, and then realized the generation of Chinese characters through algorithms. This type of method has relatively high requirements for the decomposition accuracy of Chinese characters dataset, which limits the wide application of this type of method. The current research on Chinese character generation mainly uses deep neural networks to extract the implicit features of Chinese characters, to generate higher-quality Chinese characters and overcome problems such as insufficient data sets in the early research stage. The main purpose of this article is to conduct a comprehensive and systematic review of the existing research on Chinese character generation.

Key words: handwritten Chinese character generation, shallow learning, deep learning



关键词: 手写汉字生成, 浅层学习, 深度学习