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add dataset card

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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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+
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+ # e-Callisto Solar Flare Detection Dataset
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+
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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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+ It's designed for training machine learning models to automatically detect and classify solar flares.
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+
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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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+
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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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+
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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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+
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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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+
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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.