Summary of recognition methods of Tangut characters

被引：0
作者：
Ma, Jinlin [1 ,2 ]
Yan, Qi [1 ]
Ma, Ziping [3 ]
Hao, Chaohua [1 ]
Wan, Yuetong [1 ]
机构：
[1] School of Computer Science and Engineering, North Minzu University, Yinchuan
[2] Key Laboratory for Inteligent Processing of Computer Images and Graphics, The National Ethnic Affairs Commission, Yinchuan
[3] School of Mathematics and Information Science, North Minzu University, Yinchuan
来源：
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2024年 / 52卷 / 11期
关键词：
dataset; deep learning; image recognition; neural network; Tangut character recognition;
D O I：
10.13245/j.hust.241103
中图分类号：
学科分类号：
摘要：
Aiming at the current challenges in Tangut studies，which were largely constrained by the accuracy and efficiency of Tangut character recognition，existing Tangut character recognition methods were reviewed and organized．A detailed analysis of the advantages and disadvantages of various methods was provided，and the prospects of these methods in the field of Tangut character recognition were discussed．Accurate and efficient recognition of Tangut characters was fundamental to Tangut studies．First，the main Tangut character datasets were introduced，providing foundational data for subsequent research．Then，from both traditional methods and deep learning methods perspectives，Tangut character recognition methods were summarized and analyzed，focusing on the basic principles，improvements，and advantages and disadvantages of various methods，and the performances of these methods were compared．Finally，the challenges faced by Tangut character recognition and the future research trends were discussed． © 2024 Huazhong University of Science and Technology. All rights reserved.
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页码：15 / 30
页数：15
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