Knowledge management system National Space Science Center,CAS
Classification of Spectrum Images of Solar Radio Bursts Based on Deep Learning | |
Alternative Title | WOS:000557886100050 |
Xu, Xirong1,3; Wang, Zhiyang; Hong, Yu; Xia, Tianfan; Cheng, Jun1,2; Jiang, Jingqing3 | |
Source Publication | 2019 15TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS 2019) |
2019 | |
Pages | 241-246 |
DOI | 10.1109/CIS.2019.00058 |
Language | 英语 |
ISBN | 978-1-7281-6092-4 |
Abstract | Violent solar eruptions, such as solar flares and sundial jets, will have a serious impact on the Earth. Not only does it disrupt communication facilities and navigation equipment, but also produce a large number of radio phenomena. Further research on the solar radio phenomena will help us to understand of the activities of solar energy. With the rapid development of deep learning, the feature extraction and classification identification of solar radio spectrum images based on deep learning technology have been widely used. In this paper, gamma transformation, channel normalization, gray stretching, background suppression, image denoising and other image processing techniques, are used to preprocess the spectrum image of solar radio burst. Then we use CNN model, CNN-Capsule model and CNN-LSTM model to research the classification of spectrum images of solar radio burst types. The experimental results show that our approach can effectively improve the classification effect of solar radio burst types. |
Keyword | solar radio Deep learning Image classification Digital image processing Capsule Networks CNN LSTM |
Conference Name | 15th International Conference on Computational Intelligence and Security (CIS) |
Conference Date | DEC 13-16, 2019 |
Conference Place | Macao, PEOPLES R CHINA |
Indexed By | CPCI |
Citation statistics | |
Document Type | 会议论文 |
Identifier | http://ir.nssc.ac.cn/handle/122/7766 |
Collection | 中国科学院国家空间科学中心 |
Affiliation | 1.Dalian Univ Technol, Sch Comp Sci & Technol, Dalian 116024, Peoples R China 2.Natl Astron Observ, CAS Key Lab Solar Act, Beijing 100101, Peoples R China 3.Chinese Acad Sci, State Key Lab Space Weather, Beijing 100190, Peoples R China 4.Inner Mongolia Univ Nationalities, Sch Comp Sci & Technol, Tongliao, Inner Mongolia, Peoples R China |
Recommended Citation GB/T 7714 | Xu, Xirong,Wang, Zhiyang,Hong, Yu,et al. Classification of Spectrum Images of Solar Radio Bursts Based on Deep Learning[C],2019:241-246. |
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