手写汉字识别(Handwritten Chinese character recognition,HCCR)是模式识别的一个重要研究领域,最近几十年来得到了广泛的研究与关注,随着深度学习新技术的出现,近年来基于深度学习的手写汉字识别在方法和性能上得到了突破性的进展.本文综述了深度学习在手写汉字识别领域的研究进展及具体应用.首先介绍了手写汉字识别的研究背景与现状.其次简要概述了深度学习的几种典型结构模型并介绍了一些主流的开源工具,在此基础上详细综述了基于深度学习的联机和脱机手写汉字识别的方法,阐述了相关方法的原理、技术细节、性能指标等现状情况,最后进行了分析与总结,指出了手写汉字识别领域仍需要解决的问题及未来的研究方向.
【英文摘要】
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...
由于在拍照文档、支票、表单表格、证件、邮政信封、票据、手稿文书等光学字符识别(Optical
character recognition,OCR)图像识别系统以及手写文字输入设备中的广泛应用前景,自从上个世纪80年代以来,手写汉字识别(Handwritten Chinesecharacter recognition,HCCR)一直是模式识