Datasets:
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README.md
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---
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license:
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---
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license: openrail
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task_categories:
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- image-segmentation
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tags:
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- climate
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size_categories:
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- n<1K
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---
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# Dataset Card for South Africa Crop Type Clouds
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<!-- Provide a quick summary of the dataset. -->
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This dataset contains the cloud masks generated and used for the paper [KAN You See It? KANs and Sentinel for Effective and Explainable Crop Field Segmentation](https://arxiv.org/abs/2408.07040).
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- **Curated by:** Daniele Rege Cambrin
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- **License:** OpenRAIL
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## Uses
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<!-- Address questions around how the dataset is intended to be used. -->
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The dataset will provide a quality assessment for Sentinel-2 images of the South Africa Crop Type dataset.
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Since MSI is ineffective through clouds, it was used to exclude samples that contain a large portion of the area of interest covered by clouds.
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## Dataset Structure
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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[More Information Needed]
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## Dataset Creation
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The masks are created automatically using the [s2cloudless library](https://pypi.org/project/s2cloudless/) using the algorithm presented by [Sergii Skakun et. al](https://doi.org/10.1016/j.rse.2022.112990).
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The missing bands are replaced with a channel with no-data value (0) to avoid the algorithm relying on this channel for the prediction.
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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Since no human expert is involved in the process, some annotations could be inaccurate or unreliable.
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The masks are intended to exclude samples that could be under a certain degree of uncertainty noise, and that cannot be annotated by a human expert, too.
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They should not be used outside this scope.
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## Citation
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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If you use this dataset in your work, consider citing our work.
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**BibTeX:**
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```bibtex
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@misc{cambrin2024kanitkanssentinel,
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title={KAN You See It? KANs and Sentinel for Effective and Explainable Crop Field Segmentation},
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author={Daniele Rege Cambrin and Eleonora Poeta and Eliana Pastor and Tania Cerquitelli and Elena Baralis and Paolo Garza},
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year={2024},
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eprint={2408.07040},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2408.07040},
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}
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```
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