# Dataset Card for "UC_Merced_LandUse_MultiLabel"

## Dataset Description

- **Paper:** [Bag-of-visual-words and spatial extensions for land-use classification](https://dl.acm.org/doi/pdf/10.1145/1869790.1869829)
- **Paper:** [Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method](https://ieeexplore.ieee.org/iel7/36/4358825/08089668.pdf)

### Licensing Information

Public Domain; “Map services and data available from U.S. Geological Survey, National Geospatial Program.”


## Citation Information
Imagery:

[Bag-of-visual-words and spatial extensions for land-use classification](https://dl.acm.org/doi/pdf/10.1145/1869790.1869829)

Multilabels:

[Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method](https://ieeexplore.ieee.org/iel7/36/4358825/08089668.pdf)
```
@inproceedings{yang2010bag,
  title        = {Bag-of-visual-words and spatial extensions for land-use classification},
  author       = {Yang, Yi and Newsam, Shawn},
  year         = 2010,
  booktitle    = {Proceedings of the 18th SIGSPATIAL international conference on advances in geographic information systems},
  pages        = {270--279}
}
@article{8089668,
  title        = {Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method},
  author       = {Chaudhuri, Bindita and Demir, Begüm and Chaudhuri, Subhasis and Bruzzone, Lorenzo},
  year         = 2018,
  journal      = {IEEE Transactions on Geoscience and Remote Sensing},
  volume       = 56,
  number       = 2,
  pages        = {1144--1158},
  doi          = {10.1109/TGRS.2017.2760909}
}
```
license:other region:us
{"license": "other", "dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "label", "sequence": {"class_label": {"names": {"0": "airplane", "1": "bare soil", "2": "buildings", "3": "cars", "4": "chaparral", "5": "court", "6": "dock", "7": "field", "8": "grass", "9": "mobile home", "10": "pavement", "11": "sand", "12": "sea", "13": "ship", "14": "tanks", "15": "trees", "16": "water"}}}}], "splits": [{"name": "train", "num_bytes": 438859816.5, "num_examples": 2100}], "download_size": 416309630, "dataset_size": 438859816.5}}
TAGS
#license-other #region-us 

# Dataset Card for "UC_Merced_LandUse_MultiLabel"

## Dataset Description

- Paper: Bag-of-visual-words and spatial extensions for land-use classification
- Paper: Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method

### Licensing Information

Public Domain; “Map services and data available from U.S. Geological Survey, National Geospatial Program.”



Imagery:

Bag-of-visual-words and spatial extensions for land-use classification

Multilabels:

Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method

# Dataset Card for "UC_Merced_LandUse_MultiLabel" ## Dataset Description

- Paper: Bag-of-visual-words and spatial extensions for land-use classification
- Paper: Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method ### Licensing Information

Public Domain; “Map services and data available from U.S. Geological Survey, National Geospatial Program.”



Imagery:

Bag-of-visual-words and spatial extensions for land-use classification

Multilabels:

Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method
TAGS
#license-other #region-us 
 # Dataset Card for "UC_Merced_LandUse_MultiLabel" ## Dataset Description

- Paper: Bag-of-visual-words and spatial extensions for land-use classification
- Paper: Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method ### Licensing Information

Public Domain; “Map services and data available from U.S. Geological Survey, National Geospatial Program.”



Imagery:

Bag-of-visual-words and spatial extensions for land-use classification

Multilabels:

Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method