Liu 刘, J佳 orcid.org/0000-0003-2569-1840, Ji 季, C春 orcid.org/0009-0006-4430-7882, Wang 王, Y宜 orcid.org/0000-0002-8835-3825 et al. (5 more authors) (2024) Improving the automated coronal jet identification with U-NET. The Astrophysical Journal, 972 (2). 187. ISSN 0004-637X
Abstract
Coronal jets are one of the most common eruptive activities in the solar atmosphere. They are related to rich physics processes, including, but not limited to, magnetic reconnection, flaring, instabilities, and plasma heating. Automated identification of off-limb coronal jets has been difficult due to their abundant nature, complex appearance, and relatively small size compared to other features in the corona. In this paper, we present an automated jet identification algorithm (AJIA) that utilizes true and fake jets previously detected by a laborious semiautomated jet detection algorithm (SAJIA) as the input of an image segmentation neural network U-NET. It is found that AJIA can achieve a much higher (0.81) detecting precision than SAJIA (0.34) while giving the possibility of whether each pixel in an input image belongs to a jet. We demonstrate that with the aid of artificial neural networks, AJIA can enable fast, accurate, and real-time off-limb coronal jet identification from Solar Dynamics Observatory/Atmospheric Imaging Assembly 304 Å observations, which are essential in studying the collective and long-term behavior of coronal jets and their relation to the solar activity cycles.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024. The Author(s). Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Solar activity (1475); Plasma jets (1263); Neural networks (1933); Observational astronomy (1145); Astronomy image processing (2306); Solar cycle (1487) |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematical and Physical Sciences |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Sep 2024 08:04 |
Last Modified: | 17 Sep 2024 08:04 |
Status: | Published |
Publisher: | American Astronomical Society |
Refereed: | Yes |
Identification Number: | 10.3847/1538-4357/ad66be |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:217258 |