Deep Active Learning–Based Classification of Solar Radio Spectrogram Data
The study of solar burst activity can provide early warnings for the environmental protection of the solar–terrestrial space environment. With the improvement of solar radio observation techniques, observation devices have generated enormous amounts of observation data. To solve the shortcomings of...
Saved in:
Main Authors: | Yan Liu, HongQiang Song, FaBao Yan, YanRui Su |
---|---|
Format: | Article |
Language: | English |
Published: |
IOP Publishing
2025-01-01
|
Series: | The Astrophysical Journal Supplement Series |
Subjects: | |
Online Access: | https://doi.org/10.3847/1538-4365/adda30 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A 50–55 GHz Millimeter-wave Radiometer Spectrometer for Solar Flare Detection
by: XiaoFeng Xu, et al.
Published: (2025-01-01) -
Discovery of a Periodic Radio Signal from the Formerly Radio-quiet γ-Ray Pulsar J0359+5414 with FAST
by: Ruobin Ding, et al.
Published: (2025-01-01) -
The Digital Down Converters for a Radio Astronomy Data Acquisition Systems
by: N. E. Koltsov, et al.
Published: (2017-10-01) -
Small-scale Inhomogeneity Effects on Coherent Solar Radio Emission
by: Xiaowei Zhou, et al.
Published: (2025-01-01) -
SunRISE Ground Radio Lab: Monitoring Solar Radio Bursts With an Expansive Array of Antennae at High Schools Nationwide
by: M. Akhavan‐Tafti, et al.
Published: (2025-06-01)