自动化学报2016，Vol.42Issue(8)：1125-1141,17.DOI:10.16383/j.aas.2016.c150725
深度学习在手写汉字识别中的应用综述
Applications of Deep Learning for Handwritten Chinese Character Recognition:A Review
摘要
Abstract
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.关键词
深度学习/手写汉字识别/卷积神经网络/回归神经网络/长短时记忆模型/层叠自动编码机Key words
Deep learning/handwritten Chinese character recognition (HCCR)/convolutional neural network/recurrent neural network/long-short term memory (LSTM)/stacked auto-encoder引用本文复制引用
金连文,钟卓耀,杨钊,杨维信,谢泽澄,孙俊..深度学习在手写汉字识别中的应用综述[J].自动化学报,2016,42(8):1125-1141,17.基金项目
Manuscript received November 4,2015 （）
accepted April 18,2016国家自然科学基金(61472144),广东省科技计划(2014A010103012,2015B010101004,2015B010130003,2015B010131004)资助 （61472144）
