# dSprites EuroSAT (Test set only)

Original paper: [EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification](https://arxiv.org/abs/1709.00029)

Homepage: https://github.com/phelber/EuroSAT

Bibtex:
```
@article{helber2019eurosat,
  title={Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification},
  author={Helber, Patrick and Bischke, Benjamin and Dengel, Andreas and Borth, Damian},
  journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year={2019},
  publisher={IEEE}
}
@inproceedings{helber2018introducing,
  title={Introducing EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification},
  author={Helber, Patrick and Bischke, Benjamin and Dengel, Andreas and Borth, Damian},
  booktitle={IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium},
  pages={204--207},
  year={2018},
  organization={IEEE}
}
```
arxiv:1709.00029 region:us
{}
TAGS
#arxiv-1709.00029 #region-us 

# dSprites EuroSAT (Test set only)

Original paper: EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification

Homepage: URL

Bibtex:

# dSprites EuroSAT (Test set only)

Original paper: EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification

Homepage: URL

Bibtex:
TAGS
#arxiv-1709.00029 #region-us 
 # dSprites EuroSAT (Test set only)

Original paper: EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification

Homepage: URL

Bibtex:
passage: TAGS
#arxiv-1709.00029 #region-us 
# dSprites EuroSAT (Test set only)

Original paper: EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification

Homepage: URL

Bibtex: