Datasets:

tanganke
/

eurosat

	---
	language:
	- en
	size_categories:
	- 10K<n<100K
	task_categories:
	- image-classification
	dataset_info:
	features:
	- name: image
	dtype: image
	- name: label
	dtype:
	class_label:
	names:
	'0': annual crop land
	'1': forest
	'2': brushland or shrubland
	'3': highway or road
	'4': industrial buildings or commercial buildings
	'5': pasture land
	'6': permanent crop land
	'7': residential buildings or homes or apartments
	'8': river
	'9': lake or sea
	splits:
	- name: train
	num_bytes: 70654720.8
	num_examples: 21600
	- name: test
	num_bytes: 8626053.5
	num_examples: 2700
	- name: contrast
	num_bytes: 2577694.4
	num_examples: 2700
	- name: gaussian_noise
	num_bytes: 4344552.8
	num_examples: 2700
	- name: impulse_noise
	num_bytes: 4551961.4
	num_examples: 2700
	- name: jpeg_compression
	num_bytes: 2879624.6
	num_examples: 2700
	- name: motion_blur
	num_bytes: 2881150.1
	num_examples: 2700
	- name: pixelate
	num_bytes: 2114682.2
	num_examples: 2700
	- name: spatter
	num_bytes: 4174215.2
	num_examples: 2700
	download_size: 98645265
	dataset_size: 102804655.0
	configs:
	- config_name: default
	data_files:
	- split: train
	path: data/train-*
	- split: test
	path: data/test-*
	- split: contrast
	path: data/contrast-*
	- split: gaussian_noise
	path: data/gaussian_noise-*
	- split: impulse_noise
	path: data/impulse_noise-*
	- split: jpeg_compression
	path: data/jpeg_compression-*
	- split: motion_blur
	path: data/motion_blur-*
	- split: pixelate
	path: data/pixelate-*
	- split: spatter
	path: data/spatter-*
	---


	# Dataset Card for EuroSAT

	# Dataset Source

	- [Paper with code](https://paperswithcode.com/dataset/eurosat)


	# Usage

	```python
	from datasets import load_dataset

	dataset = load_dataset('tranganke/eurosat')
	```


	### Data Fields

	The dataset contains the following fields:

	- `image`: An image in RGB format.
	- `label`: The label for the image, which is one of 10 classes:
	- 0: annual crop land
	- 1: forest
	- 2: brushland or shrubland
	- 3: highway or road
	- 4: industrial buildings or commercial buildings
	- 5: pasture land
	- 6: permanent crop land
	- 7: residential buildings or homes or apartments
	- 8: river
	- 9: lake or sea

	### Data Splits

	The dataset contains the following splits:

	- `train`: 21,600 examples
	- `test`: 2,700 examples
	- `contrast`: 2,700 examples
	- `gaussian_noise`: 2,700 example
	- `impulse_noise`: 2,700 examples
	- `jpeg_compression`: 2,700 examples
	- `motion_blur`: 2,700 examples
	- `pixelate`: 2,700 examples
	- `spatter`: 2,700 examples

	You can use any of the provided BibTeX entries for your reference list:

	```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},
	volume={12},
	number={7},
	pages={2217--2226},
	year={2019},
	publisher={IEEE}
	}

	@misc{yangAdaMergingAdaptiveModel2023,
	title = {{{AdaMerging}}: {{Adaptive Model Merging}} for {{Multi-Task Learning}}},
	shorttitle = {{{AdaMerging}}},
	author = {Yang, Enneng and Wang, Zhenyi and Shen, Li and Liu, Shiwei and Guo, Guibing and Wang, Xingwei and Tao, Dacheng},
	year = {2023},
	month = oct,
	number = {arXiv:2310.02575},
	eprint = {2310.02575},
	primaryclass = {cs},
	publisher = {arXiv},
	doi = {10.48550/arXiv.2310.02575},
	url = {http://arxiv.org/abs/2310.02575},
	archiveprefix = {arxiv},
	keywords = {Computer Science - Computer Vision and Pattern Recognition,Computer Science - Machine Learning}
	}

	@misc{tangConcreteSubspaceLearning2023,
	title = {Concrete {{Subspace Learning}} Based {{Interference Elimination}} for {{Multi-task Model Fusion}}},
	author = {Tang, Anke and Shen, Li and Luo, Yong and Ding, Liang and Hu, Han and Du, Bo and Tao, Dacheng},
	year = {2023},
	month = dec,
	number = {arXiv:2312.06173},
	eprint = {2312.06173},
	publisher = {arXiv},
	url = {http://arxiv.org/abs/2312.06173},
	archiveprefix = {arxiv},
	copyright = {All rights reserved},
	keywords = {Computer Science - Machine Learning}
	}


	@misc{tangMergingMultiTaskModels2024,
	title = {Merging {{Multi-Task Models}} via {{Weight-Ensembling Mixture}} of {{Experts}}},
	author = {Tang, Anke and Shen, Li and Luo, Yong and Yin, Nan and Zhang, Lefei and Tao, Dacheng},
	year = {2024},
	month = feb,
	number = {arXiv:2402.00433},
	eprint = {2402.00433},
	primaryclass = {cs},
	publisher = {arXiv},
	doi = {10.48550/arXiv.2402.00433},
	url = {http://arxiv.org/abs/2402.00433},
	archiveprefix = {arxiv},
	copyright = {All rights reserved},
	keywords = {Computer Science - Computer Vision and Pattern Recognition,Computer Science - Machine Learning}
	}
	```