Datasets:
Improve dataset card: add task category and clean up metadata
#1
by nielsr HF Staff - opened
README.md
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license: mit
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size_categories:
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tags:
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- arxiv:2606.08324
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---
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# SAE-LWIR: A MODTRAN-Generated Dataset for Atmospheric Compensation in Standoff LWIR Hyperspectral Imaging
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**Fabian Perez, Nicolas Quintero, Jeferson Acevedo, Hoover Rueda-Chacón** — Universidad Industrial de Santander, Bucaramanga, Colombia
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[Project Page](https://factral.github.io/SAE-LWIR) · [Code](https://github.com/Factral/SAE-LWIR) · [Paper](https://
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## Description
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```bibtex
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@inproceedings{perez2026setbased,
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title={Set-Based Transformer for Atmospheric Compensation in Standoff LWIR Hyperspectral Imaging},
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author={Perez, Fabian and Quintero, Nicolas and Acevedo, Jeferson and Rueda-Chac{\'o}n, Hoover},
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booktitle={IGARSS 2026 - IEEE International Geoscience and Remote Sensing Symposium},
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year={2026}
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}
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## Acknowledgments
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This work was supported by the Air Force Office of Scientific Research (AFOSR) through the Southern Office of Aerospace Research and Development (SOARD) under grant number FA8655-25-1-8010.
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---
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license: mit
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task_categories:
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- other
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size_categories:
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- 100K<n<1M
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pretty_name: SAE-LWIR — Standoff LWIR Atmospheric Compensation Dataset
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tags:
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- hyperspectral
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- LWIR
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- remote-sensing
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- atmospheric-compensation
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- radiative-transfer
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- MODTRAN
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- physics
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---
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# SAE-LWIR: A MODTRAN-Generated Dataset for Atmospheric Compensation in Standoff LWIR Hyperspectral Imaging
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**Fabian Perez, Nicolas Quintero, Jeferson Acevedo, Hoover Rueda-Chacón** — Universidad Industrial de Santander, Bucaramanga, Colombia
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[Project Page](https://factral.github.io/SAE-LWIR) · [Code](https://github.com/Factral/SAE-LWIR) · [Paper](https://huggingface.co/papers/2606.08324)
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## Description
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```bibtex
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@inproceedings{perez2026setbased,
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title={Set-Based Transformer for Atmospheric Compensation in Standoff LWIR Hyperspectral Imaging},
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author={Perez, Fabian and Quintero, Nicolas and Acevedo, Jeferson and Rueda-Chac{\\'o}n, Hoover},
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booktitle={IGARSS 2026 - IEEE International Geoscience and Remote Sensing Symposium},
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year={2026}
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}
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## Acknowledgments
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This work was supported by the Air Force Office of Scientific Research (AFOSR) through the Southern Office of Aerospace Research and Development (SOARD) under grant number FA8655-25-1-8010.
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