Affiliation:
1. College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
Abstract
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.
Funder
National Natural Science Foundation of China
Subject
Space and Planetary Science,Astronomy and Astrophysics
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献