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@@ -24,11 +24,36 @@ dataset_info:
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  '14': urban residential
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  splits:
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  - name: train
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- num_bytes: 1777210275.0
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  num_examples: 30000
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  download_size: 1263253291
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- dataset_size: 1777210275.0
 
 
 
 
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  ---
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  # Dataset Card for "GID"
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- [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  '14': urban residential
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  splits:
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  - name: train
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+ num_bytes: 1777210275
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  num_examples: 30000
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  download_size: 1263253291
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+ dataset_size: 1777210275
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+ license: other
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+ task_categories:
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+ - image-classification
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+ - zero-shot-image-classification
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  ---
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  # Dataset Card for "GID"
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+ ## Dataset Description
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+
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+ - **Paper** [Land-cover classification with high-resolution remote sensing images using transferable deep models](https://www.sciencedirect.com/science/article/pii/S0034425719303414)
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+ -
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+ ### Licensing Information
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+
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+ Public domain.
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+
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+ ## Citation Information
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+
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+ [Land-cover classification with high-resolution remote sensing images using transferable deep models](https://www.sciencedirect.com/science/article/pii/S0034425719303414)
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+
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+ ```
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+ @article{GID2020,
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+ title = {Land-cover classification with high-resolution remote sensing images using transferable deep models},
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+ author = {Tong, Xin-Yi and Xia, Gui-Song and Lu, Qikai and Shen, Huanfeng and Li, Shengyang and You, Shucheng and Zhang, Liangpei},
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+ year = 2020,
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+ journal = {Remote Sensing of Environment},
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+ volume = 237,
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+ pages = 111322
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+ }
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+ ```