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@@ -52,4 +52,16 @@ If you use the DFC2020 dataset in your work, please cite the original paper:
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  pages={3185-3199},
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  keywords={Earth;Data integration;Remote sensing;Satellites;Training;Tensors;Synthetic aperture radar;Convolutional neural networks (CNNs);deep learning;image analysis and data fusion;land-cover mapping;multimodal;random forests (RFs);weak supervision},
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  doi={10.1109/JSTARS.2021.3063849}}
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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  pages={3185-3199},
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  keywords={Earth;Data integration;Remote sensing;Satellites;Training;Tensors;Synthetic aperture radar;Convolutional neural networks (CNNs);deep learning;image analysis and data fusion;land-cover mapping;multimodal;random forests (RFs);weak supervision},
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  doi={10.1109/JSTARS.2021.3063849}}
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+ ```
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+ and if you also find our benchmark useful, please consider citing our paper:
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+ ```
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+ @misc{si2025scalablefoundationmodelmultimodal,
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+ title={Towards Scalable Foundation Model for Multi-modal and Hyperspectral Geospatial Data},
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+ author={Haozhe Si and Yuxuan Wan and Minh Do and Deepak Vasisht and Han Zhao and Hendrik F. Hamann},
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+ year={2025},
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+ eprint={2503.12843},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CV},
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+ url={https://arxiv.org/abs/2503.12843},
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+ }
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  ```