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README.md
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"coronal holes", "loops" or "flares"
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You can also choose "active regions" to get a general pool for testing.
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![NASA_SDO_Coronal_Hole](images/NASA_SDO_Coronal_Hole2.jpg)
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![NASA_SDO_Coronal_Loop](images/NASA_SDO_Coronal_Loop.jpg)
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![NASA_SDO_Solar_Flare](images/NASA_SDO_Solar_Flare.jpg)
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## How to use this Model
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"coronal holes", "loops" or "flares"
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You can also choose "active regions" to get a general pool for testing.
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### NASA_SDO_Coronal_Hole
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![NASA_SDO_Coronal_Hole](images/NASA_SDO_Coronal_Hole2.jpg)
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### NASA_SDO_Coronal_Loop
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![NASA_SDO_Coronal_Loop](images/NASA_SDO_Coronal_Loop.jpg)
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### NASA_SDO_Solar_Flare
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![NASA_SDO_Solar_Flare](images/NASA_SDO_Solar_Flare.jpg)
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## Training data
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The ViT model was pretrained on a dataset consisting of 14 million images and 21k classes ([ImageNet-21k](http://www.image-net.org/).
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More information on the base model used can be found here: (https://huggingface.co/google/vit-base-patch16-224-in21k)
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## How to use this Model
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## References
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A publication on this work is currently in preparation. In the meantime, please refer to this model by using the following citation:
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```
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@misc{sdovt2022,
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author = {Frank Soboczenski and Paul J Wright},
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title = {SDOVT: A Vision Transformer Model for Solar Dynamics Observatory (SDO) Data},
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url = {http://github.com/h21k/sdovis},
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version = {1.0},
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year = {2022},
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}
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```
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For the base ViT model used please refer to:
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```bibtex
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@misc{wu2020visual,
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title={Visual Transformers: Token-based Image Representation and Processing for Computer Vision},
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author={Bichen Wu and Chenfeng Xu and Xiaoliang Dai and Alvin Wan and Peizhao Zhang and Zhicheng Yan and Masayoshi Tomizuka and Joseph Gonzalez and Kurt Keutzer and Peter Vajda},
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year={2020},
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eprint={2006.03677},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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```
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