Single and Multiwavelength Detection of Coronal Dimming and Coronal Wave Using Faster R-CNN
Joint Authors
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-07-08
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Automatic detection of solar events, especially uncommon events such as coronal dimming (CD) and coronal wave (CW), is very important in solar physics research.
The CD and CW are not only related to the detection of coronal mass ejections (CMEs) but also affect space weather.
In this paper, we have studied methods for automatically detecting them.
In addition, we have collected and processed a dataset that includes the solar images and event records, where the solar images come from the Atmospheric Imaging Assembly (AIA) of Solar Dynamics Observatory (SDO) and the event records come from Heliophysics Event Knowledgebase (HEK).
Different from the methods used before, we introduce the idea of deep learning.
We train single-wavelength and multiwavelength models based on Faster R-CNN.
In terms of accuracy, the single-wavelength model performs better.
The multiwavelength model has a better detection performance on multiple solar events than the single-wavelength model.
American Psychological Association (APA)
Xie, Zongxia& Ji, Chunyang. 2019. Single and Multiwavelength Detection of Coronal Dimming and Coronal Wave Using Faster R-CNN. Advances in Astronomy،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1114445
Modern Language Association (MLA)
Xie, Zongxia& Ji, Chunyang. Single and Multiwavelength Detection of Coronal Dimming and Coronal Wave Using Faster R-CNN. Advances in Astronomy No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1114445
American Medical Association (AMA)
Xie, Zongxia& Ji, Chunyang. Single and Multiwavelength Detection of Coronal Dimming and Coronal Wave Using Faster R-CNN. Advances in Astronomy. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1114445
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1114445