Advances in Offline Handwritten Chinese Character Recognition : a Survey

Offline Chinese character recognition has played an indispensable role over the past decade. While it has been continuously integrated into daily life, the technology behind it has also been continuously iterated and updated. Aiming to analyse the important results of the current development of this technology as well as its development prospects, this essay will focus on the excellent results of the past development of Offline Handwritten Chinese Character Recognition (OHCCR) as well as the current status, and present an overview and insights of these technologies. Finally, the problems encountered in the research of this technology and the prospects are presented.

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Publication Details

Journal
Creativity and Innovation
Published
2025-01-01
DOI
https://doi.org/10.47297/wspciwsp2516-252712.20250902
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Advances in Offline Handwritten Chinese Character Recognition : a Survey

Liu Jun-hao
Creativity and Innovation
Handwritten Text Recognition Techniques
article

Advances in Offline Handwritten Chinese Character Recognition : a Survey

Liu Jun-hao
article en

Abstract

Offline Chinese character recognition has played an indispensable role over the past decade. While it has been continuously integrated into daily life, the technology behind it has also been continuously iterated and updated. Aiming to analyse the important results of the current development of this technology as well as its development prospects, this essay will focus on the excellent results of the past development of Offline Handwritten Chinese Character Recognition (OHCCR) as well as the current status, and present an overview and insights of these technologies. Finally, the problems encountered in the research of this technology and the prospects are presented.

Creativity and InnovationVol. 9(2)
Beijing University of Posts and Telecommunications (CN)
Openalex Percentile: Top 90%
Handwritten Text Recognition Techniques
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