RSICB Dataset

Dataset details

Last updated: 15 Dec 2022
Meta Album ID REM_SEN.RSICB
Domain ID REM_SEN
Domain Name Remote Sensing
Set Number 1
Dataset ID RSICB
Dataset Name RSICB
Short Description Remote sensing dataset
Long Description RSICB128 dataset (https://github.com/lehaifeng/RSI-CB) covers 45 scene categories, assembling in total 36 000 images of resolution 128x128 px. The data authors select various locations around the world, and follow China's landuse classification standard. This collection has 2-level label hierarchy with 6 super-categories: agricultural land, construction land and facilities, transportation and facilities, water and water conservancy facilities, woodland, and other lands. The preprocessed version of RSICB is created by resizing the images into 128x128 px using an anti-aliasing filter.
# Classes 45
# Images 36707
Keywords remote sensing, satellite image, aerial image, land cover
Data Format images
Image size 128x128
License
(original data release)		 Open for research purposes
License
(Meta-Album data release)		 CC BY-NC 4.0
License URL
(Meta-Album data release)		 https://creativecommons.org/licenses/by-nc/4.0/
Source RSI-CB: A Large Scale Remote Sensing Image Classification Benchmark via Crowdsource Data
Source URL https://github.com/lehaifeng/RSI-CB
Original Author Haifeng Li, Xin Dou, Chao Tao, Zhixiang Hou, Jie Chen, Jian Peng, Min Deng, Ling Zhao
Original contact lihaifeng@csu.edu.cn
Meta Album author Phan Anh VU
Created Date 01 March 2022
Contact Name Ihsan Ullah
Contact Email meta-album@chalearn.org
Contact URL https://meta-album.github.io/

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Dataset Info Datasheet

Download Dataset from OpenML

Dataset Version OpenML ID
Micro 44315 Download
Mini 44300 Download
Extended 44333 Download

Code to download dataset using OpenML API

      # import openml
      import openml
  
      # download dataset with DATASET_ID. DATASET_ID is OpenML ID
      dataset = openml.datasets.get_dataset(DATASET_ID)
  
      # display dataset info
      print(dataset.name)

Sample Images

Cite this dataset 

@article{li2020RSI-CB,
    title={RSI-CB: A Large-Scale Remote Sensing Image Classification Benchmark Using Crowdsourced Data},
    author={Li, Haifeng and Dou, Xin and Tao, Chao and Wu, Zhixiang and Chen, Jie and Peng, Jian and Deng, Min and Zhao, Ling},
    journal={Sensors},
    DOI = {doi.org/10.3390/s20061594},
    year={2020},
    volume = {20},
    number = {6},
    pages = {1594},
    type = {Journal Article}
}
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Cite Meta-Album

  @inproceedings{meta-album-2022,
    title={Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification},
    author={Ullah, Ihsan and Carrion, Dustin and Escalera, Sergio and Guyon, Isabelle M and Huisman, Mike and Mohr, Felix and van Rijn, Jan N and Sun, Haozhe and Vanschoren, Joaquin and Vu, Phan Anh},
    booktitle={Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
    url = {https://meta-album.github.io/},
    year = {2022}
  }
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