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README.md
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@@ -77,6 +77,8 @@ OAM-TCD is a dataset of high-resolution (10 cm/px) tree cover maps with instance
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Images in the dataset are provided as 2048x2048 px RGB GeoTIFF tiles. The dataset can be used to train both instance segmentation models and semantic segmentation models.
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### Dataset Description
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- **Curated by:** Restor / ETH Zurich
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## Citation
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If you use OAM-TCD in your own work or research, please cite our arXiv paper: and reference the dataset DOI
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**BibTeX:**
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## Dataset Card Authors
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Images in the dataset are provided as 2048x2048 px RGB GeoTIFF tiles. The dataset can be used to train both instance segmentation models and semantic segmentation models.
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For more information please read [our preprint on arXiv](https://arxiv.org/abs/2407.11743).
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### Dataset Description
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- **Curated by:** Restor / ETH Zurich
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## Citation
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If you use OAM-TCD in your own work or research, please cite our arXiv paper: and reference the dataset DOI
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**BibTeX:**
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After the paper is peer reviewed, this citation will be updated.
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```
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@misc{veitchmichaelis2024oamtcdgloballydiversedataset,
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title={OAM-TCD: A globally diverse dataset of high-resolution tree cover maps},
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author={Josh Veitch-Michaelis and Andrew Cottam and Daniella Schweizer and Eben N. Broadbent and David Dao and Ce Zhang and Angelica Almeyda Zambrano and Simeon Max},
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year={2024},
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eprint={2407.11743},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2407.11743},
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}
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```
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## Dataset Card Authors
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