Applications of deep learning for handwritten chinese character recognition: a review

作者：Jin, Lian-Wen^*; Zhong, Zhuo-Yao; Yang, Zhao; Yang, Wei-Xin; Xie, Ze-Cheng; Sun, Jun

来源：Acta Automatica Sinica, 2016, 42(8): 1125-1141.

DOI：10.16383/j.aas.2016.c150725

• Auto encoders
• Convolutional neural network
• Handwritten chinese character recognition
• Learning models
• Open source tools
• Performance analysis
• State of the art
• Technical details

Handwritten Chinese character recognition (HCCR) is an important research filed of pattern recognition, which has attracted extensive studies during the past decades. With the emergence of deep learning, new breakthrough progresses of HCCR have been obtained in recent years. In this paper, we review the applications of deep learning models in the field of HCCR. First, the research background and current state-of-the-art HCCR technologies are introduced. Then, we provide a brief overview of several typical deep learning models, and introduce some widely used open source tools for deep learning. The approaches of online HCCR and offline HCCR based on deep learning are surveyed, with the summaries of the related methods, technical details, and performance analysis. Finally, further research directions are discussed.

• 出版日期2016-8-1
• 单位华南理工大学