Data for Loosen Attention Experiments

Citation Author(s):
Qian
Wang
Submitted by:
Qian Wang
Last updated:
Sun, 03/30/2025 - 22:33
DOI:
10.21227/exxa-2v12
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Abstract 

<p>This comprehensive dataset combines all-sky auroral observations with high-resolution small-scale auroral data and is a resource for space weather research, magnetospheric studies and atmospheric science. The captured all-sky dataset classifies auroral displays into four different morphological types: arcs (smooth, curtain-like structures), folds (folded, undulating structures), radial corona (ray projections from a central point) and hotspots (locally bright regions). The accompanying small-scale dataset provides detailed images of fine auroral structures, which help to analyse microphysical processes. The dataset supports the training of machine learning models for auroral classification and auroral target detection.</p>

Instructions: 

<p>This comprehensive dataset combines all-sky auroral observations with high-resolution small-scale auroral data and is a resource for space weather research, magnetospheric studies and atmospheric science. There are a total of 4,000 training data in it for the all-sky auroral images for the model to learn what is useful during the training process.</p>

Comments

The dataset supports machine learning models for auroral classification and auroral target detection.

Submitted by Qian Wang on Sun, 03/30/2025 - 22:34

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