| --- |
| license: |
| - unknown |
| task_categories: |
| - image-classification |
| language: |
| - en |
| tags: |
| - remote-sensing |
| - earth-observation |
| - geospatial |
| - satellite-imagery |
| - scene-classification |
| pretty_name: RSSCN7 |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # RSSCN7 |
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|  |
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| ## Description |
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| The RSSCN7 dataset is designed for scene classification tasks and provides a collection of high-resolution RGB images. This dataset comprises a total of 2,800 images, each with a resolution of 400x400 pixels. The images are extracted from [Google Earth](https://earth.google.com/web/) and cover a range of diverse scenes. RSSCN7 includes seven distinct scene classes, with 400 images per class. |
|
|
| ## Details |
|
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| ### Statistics |
| - Total Number of Images: 2,800 |
| - Image Resolution: 400x400 pixels |
| - Scene Classes: 7 |
| - Dataset Size: 0.36GB |
|
|
| ## Citation |
|
|
| If you use the RSSCN7 dataset in your research, please consider citing the following publication or the dataset's official website: |
|
|
| ```bibtex |
| @article{7272047, |
| title = {Deep Learning Based Feature Selection for Remote Sensing Scene Classification}, |
| author = {Zou, Qin and Ni, Lihao and Zhang, Tong and Wang, Qian}, |
| year = 2015, |
| journal = {IEEE Geoscience and Remote Sensing Letters}, |
| volume = 12, |
| number = 11, |
| pages = {2321--2325}, |
| doi = {10.1109/LGRS.2015.2475299} |
| } |
| ``` |
|
|
| - Paper with code: https://paperswithcode.com/dataset/rsscn7 |
| - Repo: https://github.com/palewithout/RSSCN7 |
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