Sunspot drawings handwritten character recognition method based on deep learning | |
Zheng, Sheng1; Zeng, Xiangyun1; Lin, Ganghua2; Zhao, Cui2; Feng YL(冯永利)3; Tao JP(陶金萍)3; Zhu, Daoyuan1; Xiong, Li1 | |
发表期刊 | NEW ASTRONOMY |
2016-05-01 | |
卷号 | 45页码:54-59 |
DOI | 10.1016/j.newast.2015.11.001 |
产权排序 | 第3完成单位 |
收录类别 | SCI |
关键词 | Sunspot Drawings Convolution Neural Network Handwriting Character Recognition |
摘要 | High accuracy scanned sunspot drawings handwritten characters recognition is an issue of critical importance to analyze sunspots movement and store them in the database. This paper presents a robust deep learning method for scanned sunspot drawings handwritten characters recognition. The convolution neural network (CNN) is one algorithm of deep learning which is truly successful in training of multi-layer network structure. CNN is used to train recognition model of handwritten character images which are extracted from the original sunspot drawings. We demonstrate the advantages of the proposed method on sunspot drawings provided by Chinese Academy Yunnan Observatory and obtain the daily full-disc sunspot numbers and sunspot areas from the sunspot drawings. The experimental results show that the proposed method achieves a high recognition accurate rate. (C) 2015 Elsevier B.V. All rights reserved. |
资助项目 | National Natural Science Fund Committee ; Chinese Academy of Sciences astronomical union funds[U1331113] ; Chinese Academy of Sciences astronomical union funds[2014FY120300] |
项目资助者 | National Natural Science Fund Committee ; Chinese Academy of Sciences astronomical union funds[U1331113, 2014FY120300] |
语种 | 英语 |
学科领域 | 天文学 ; 太阳与太阳系 |
文章类型 | Article |
出版者 | ELSEVIER SCIENCE BV |
出版地 | PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS |
ISSN | 1384-1076 |
URL | 查看原文 |
WOS记录号 | WOS:000369200700009 |
WOS研究方向 | Astronomy & Astrophysics |
WOS类目 | Astronomy & Astrophysics |
关键词[WOS] | CATALOG |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ynao.ac.cn/handle/114a53/9325 |
专题 | 太阳物理研究组 |
通讯作者 | Zeng, Xiangyun |
作者单位 | 1.College of Science, China Three Gorges University, Yichang 443002, China 2.Key Laboratory of Solar Activity, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China 3.Yunnan Observatories, Chinese Academy of Sciences, P.O. Box 110, Kunming, Yunnan 650011, China |
推荐引用方式 GB/T 7714 | Zheng, Sheng,Zeng, Xiangyun,Lin, Ganghua,et al. Sunspot drawings handwritten character recognition method based on deep learning[J]. NEW ASTRONOMY,2016,45:54-59. |
APA | Zheng, Sheng.,Zeng, Xiangyun.,Lin, Ganghua.,Zhao, Cui.,Feng YL.,...&Xiong, Li.(2016).Sunspot drawings handwritten character recognition method based on deep learning.NEW ASTRONOMY,45,54-59. |
MLA | Zheng, Sheng,et al."Sunspot drawings handwritten character recognition method based on deep learning".NEW ASTRONOMY 45(2016):54-59. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Sunspot drawings han(2452KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 请求全文 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论