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--- |
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task_categories: |
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- image-classification |
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tags: |
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- astrophysics |
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- flares |
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- solar flares |
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- sun |
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pretty_name: e-Callisto Solar Flare Detection |
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size_categories: |
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- 100K<n<1M |
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--- |
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# e-Callisto Solar Flare Detection Dataset |
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[Institute of Data Science i4Ds, FHNW](https://i4ds.ch)<br> |
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Compiled by [Gabriel Torres Gamez | StellarMilk](https://huggingface.co/StellarMilk) |
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## Overview |
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This dataset comprises radio spectra from the [e-Callisto solar spectrometer network](https://www.e-callisto.org/index.html), annotated based on [labels from the e-Callisto database](http://soleil.i4ds.ch/solarradio/data/BurstLists/2010-yyyy_Monstein/). |
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The data was downloaded using the [ecallisto_ng Package](https://github.com/i4Ds/ecallisto_ng). It's designed for training machine learning models to automatically detect and classify solar flares. |
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## Data Collection |
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Data has been collected from various stations, with the following date ranges: |
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| Station | Date Range | |
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|-------------------|--------------------------| |
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| Australia-ASSA_01 | 2021-02-13 to 2021-12-11 | |
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| Australia-ASSA_02 | 2021-02-13 to 2021-12-09 | |
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| Australia-ASSA_62 | 2021-12-10 to 2023-12-12 | |
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| Australia-ASSA_63 | 2021-12-10 to 2023-12-12 | |
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## Data Augmentation |
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Due to the rarity of solar flares, we've augmented the dataset by padding the time series data around each flare event. |
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## Caution |
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The dataset underwent preprocessing and certain assumptions were made for label cleanup. Be aware of potential inaccuracies in the labels. |
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## Split Recommendations |
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The dataset doesn't include predefined train-validation-test splits. When creating splits, ensure augmented data does not overlap between training and validation/test sets to avoid data leakage. |
