中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 国家天文台
  3. 中国科学院国家天文台
Solar Filament Recognition Based on Deep Learning

文献类型：期刊论文

作者Zhu, Gaofei1,2,3; Lin, Ganghua1,3; Wang, Dongguang1,3; Liu, Suo1,3,4; Yang, Xiao1,3
刊名SOLAR PHYSICS
出版日期2019-09-01
卷号294期号:9页码:13
关键词Filaments Prominences Image processing Deep learning
ISSN号0038-0938
DOI10.1007/s11207-019-1517-4
英文摘要The paper presents a reliable method using deep learning to recognize solar filaments in H alpha full-disk solar images automatically. This method cannot only identify filaments accurately but also minimize the effects of noise points of the solar images. Firstly, a raw filament dataset is set up, consisting of tens of thousands of images required for deep learning. Secondly, an automated method for solar filament identification is developed using the U-Net deep convolutional network. To test the performance of the method, a dataset with 60 pairs of manually corrected H alpha images is employed. These images are obtained from the Big Bear Solar Observatory/Full-Disk H-alpha Patrol Telescope (BBSO/FDHA) in 2013. Cross-validation indicates that the method can efficiently identify filaments in full-disk H alpha images.
WOS关键词ERUPTIONS
资助项目National Science Foundation of China[u1531247] ; National Science Foundation of China[11427901] ; 13th Five-year Informatization Plan of Chinese Academy of Sciences[XXH13505-04] ; special foundation work of the Ministry of Science and Technology of China[2014fy120300]
WOS研究方向Astronomy & Astrophysics
语种英语
WOS记录号WOS:000485884300002
出版者SPRINGER
资助机构National Science Foundation of China ; National Science Foundation of China ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; special foundation work of the Ministry of Science and Technology of China ; special foundation work of the Ministry of Science and Technology of China ; National Science Foundation of China ; National Science Foundation of China ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; special foundation work of the Ministry of Science and Technology of China ; special foundation work of the Ministry of Science and Technology of China ; National Science Foundation of China ; National Science Foundation of China ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; special foundation work of the Ministry of Science and Technology of China ; special foundation work of the Ministry of Science and Technology of China ; National Science Foundation of China ; National Science Foundation of China ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; 13th Five-year Informatization Plan of Chinese Academy of Sciences ; special foundation work of the Ministry of Science and Technology of China ; special foundation work of the Ministry of Science and Technology of China
源URL[http://ir.bao.ac.cn/handle/114a11/27704]  
专题中国科学院国家天文台
通讯作者Zhu, Gaofei
作者单位1.Chinese Acad Sci, Natl Astron Observ, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Natl Astron Observ, Key Lab Solar Act, Beijing 100101, Peoples R China
4.Univ Chinese Acad Sci, Sch Astron & Space Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Zhu, Gaofei,Lin, Ganghua,Wang, Dongguang,et al. Solar Filament Recognition Based on Deep Learning[J]. SOLAR PHYSICS,2019,294(9):13.
APA Zhu, Gaofei,Lin, Ganghua,Wang, Dongguang,Liu, Suo,&Yang, Xiao.(2019).Solar Filament Recognition Based on Deep Learning.SOLAR PHYSICS,294(9),13.
MLA Zhu, Gaofei,et al."Solar Filament Recognition Based on Deep Learning".SOLAR PHYSICS 294.9(2019):13.

入库方式： OAI收割

来源：国家天文台

浏览0
下载0
收藏0
其他版本

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。