https://github.com/i4ds/fcd
Last synced: 11 months ago
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- Host: GitHub
- URL: https://github.com/i4ds/fcd
- Owner: i4Ds
- Created: 2025-05-14T10:43:58.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-11T12:19:33.000Z (about 1 year ago)
- Last Synced: 2025-06-18T01:51:28.054Z (about 1 year ago)
- Language: Python
- Size: 308 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# FCD: Fourier Convolutional Decoder
FCD is designed to work with STIX data; it takes 48 Fourier components (24 real, 24 imaginary) and reconstructs the image corresponding to them.
Below is the comparison of the FCD with other popular STIX reconstruction alorithms.
# Running the Project
`pip install -r requirements.txt` to install all the necessary packages.
# Project Bits and Pieces
- [nn](nn/) includes [training](nn/train/) and [testing](nn/test/) of the FCD.
- [metrics](metrics/), [data](data/), and [utils](utils/) include relevant utility functions of the project.
**[Pretrained model](https://huggingface.co/mervess/FCD-Solar) of the FCD and a [demo](https://huggingface.co/spaces/mervess/FCD-Solar-Demo) of the model are available on HuggingFace.**
# Data
- Refer to [STIX data center](https://datacenter.stix.i4ds.net) to use observational STIX data.
- Refer to [STIX data generator](https://github.com/i4Ds/stix-data-generator) to generate your own simulated data.
# Citation
If this repository proves useful for your research, please cite our work as follows.
```
@article{SelcukSimsek2025,
author = {Selcuk-Simsek, Merve and Massa, Paolo and Xiao, Hualin and Krucker, S{\"a}m and Csillaghy, Andr{\'e}},
title = {Fourier convolutional decoder: reconstructing solar flare images via deep learning},
journal = {Neural Computing and Applications},
pages = {1--32},
year = {2025},
publisher = {Springer}
doi = {10.1007/s00521-025-11283-6},
url = {https://doi.org/10.1007/s00521-025-11283-6}
}
```