Datasetpublic

timm/resisc45

Description RESISC45 dataset is a publicly available benchmark for Remote Sensing Image Scene Classification (RESISC), created by Northwestern Polytechnical University (NWPU). This dataset contains 31,500 images, covering 45 scene classes with 700 images in each class. The dataset does not have any default splits. Train, validation, and test splits were based on these definitions here… See the full description on the dataset page: https://huggingface.co/datasets/timm/resisc45.

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Description

RESISC45 dataset is a publicly available benchmark for Remote Sensing Image Scene Classification (RESISC), created by Northwestern Polytechnical University (NWPU). This dataset contains 31,500 images, covering 45 scene classes with 700 images in each class.

The dataset does not have any default splits. Train, validation, and test splits were based on these definitions here https://github.com/google-research/google-research/blob/master/remotesensingrepresentations/README.md#dataset-splits

—Paper: https://arxiv.org/abs/1703.00121.
—Website: https://paperswithcode.com/dataset/resisc45 (original homepage is unresponsive http://www.escience.cn/people/JunweiHan/NWPU-RESISC45.html)

Citation

bibtex

@article{Cheng_2017,
   title={Remote Sensing Image Scene Classification: Benchmark and State of the Art},
   volume={105},
   ISSN={1558-2256},
   url={http://dx.doi.org/10.1109/JPROC.2017.2675998},
   DOI={10.1109/jproc.2017.2675998},
   number={10},
   journal={Proceedings of the IEEE},
   publisher={Institute of Electrical and Electronics Engineers (IEEE)},
   author={Cheng, Gong and Han, Junwei and Lu, Xiaoqiang},
   year={2017},
   month={Oct},
   pages={1865-1883}
}