DEVELOPMENT... { "data_id": "44341", "name": "Meta_Album_RSD_Extended", "exact_name": "Meta_Album_RSD_Extended", "version": 1, "version_label": null, "description": "## **Meta-Album RSD Dataset (Extended)**\n***\nRSD46 dataset (https:\/\/github.com\/RSIA-LIESMARS-WHU\/RSD46-WHU) is collected from Google Earth and Tianditu. The collection contains 46 scene categories, with a total of 117 000 images. Each scene category has between 500 - 3000 images. The original resolution are 256x256 px or 512x512 px. We have created preprocessed version of RSD for Meta-Album by resizing the original dataset to 128x128 px. \n\n\n\n### **Dataset Details**\n![](https:\/\/meta-album.github.io\/assets\/img\/samples\/RSD.png)\n\n**Meta Album ID**: REM_SEN.RSD \n**Meta Album URL**: [https:\/\/meta-album.github.io\/datasets\/RSD.html](https:\/\/meta-album.github.io\/datasets\/RSD.html) \n**Domain ID**: REM_SEN \n**Domain Name**: Remote Sensing \n**Dataset ID**: RSD \n**Dataset Name**: RSD \n**Short Description**: Remote sensing dataset \n**\\# Classes**: 43 \n**\\# Images**: 43825 \n**Keywords**: remote sensing, satellite image, aerial image, land cover \n**Data Format**: images \n**Image size**: 128x128 \n\n**License (original data release)**: Open for research and non-profit purposes \n**License (Meta-Album data release)**: CC BY-NC 4.0 \n**License URL (Meta-Album data release)**: [https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/](https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/) \n\n**Source**: RSD46-WHU \n**Source URL**: https:\/\/github.com\/RSIA-LIESMARS-WHU\/RSD46-WHU \n \n**Original Author**: Yang Long, Yiping Gong, Zhifeng Xiao, and Qing Liu, Deren Li, Chunshan Wei, Gefu Tang and Junyi Liu \n**Original contact**: longyang@whu.edu.cn \n\n**Meta Album author**: Phan Anh VU \n**Created Date**: 01 March 2022 \n**Contact Name**: Ihsan Ullah \n**Contact Email**: meta-album@chalearn.org \n**Contact URL**: [https:\/\/meta-album.github.io\/](https:\/\/meta-album.github.io\/) \n\n\n\n### **Cite this dataset**\n```\n@ARTICLE{7827088,\n author={Long, Yang and Gong, Yiping and Xiao, Zhifeng and Liu, Qing},\n journal={IEEE Transactions on Geoscience and Remote Sensing}, \n title={Accurate Object Localization in Remote Sensing Images Based on Convolutional Neural Networks}, \n year={2017},\n volume={55},\n number={5},\n pages={2486-2498},\n doi={10.1109\/TGRS.2016.2645610}}\n\n@article{xiao2017high,\n title={High-resolution remote sensing image retrieval based on CNNs from a dimensional perspective},\n author={Xiao, Zhifeng and Long, Yang and Li, Deren and Wei, Chunshan and Tang, Gefu and Liu, Junyi},\n journal={Remote Sensing},\n volume={9},\n number={7},\n pages={725},\n year={2017},\n publisher={Multidisciplinary Digital Publishing Institute}\n}\n```\n\n\n### **Cite Meta-Album**\n```\n@inproceedings{meta-album-2022,\n title={Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification},\n 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},\n booktitle={Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},\n url = {https:\/\/meta-album.github.io\/},\n year = {2022}\n }\n```\n\n\n### **More**\nFor more information on the Meta-Album dataset, please see the [[NeurIPS 2022 paper]](https:\/\/meta-album.github.io\/paper\/Meta-Album.pdf) \nFor details on the dataset preprocessing, please see the [[supplementary materials]](https:\/\/openreview.net\/attachment?id=70_Wx-dON3q&name=supplementary_material) \nSupporting code can be found on our [[GitHub repo]](https:\/\/github.com\/ihsaan-ullah\/meta-album) \nMeta-Album on Papers with Code [[Meta-Album]](https:\/\/paperswithcode.com\/dataset\/meta-album) \n\n\n\n### **Other versions of this dataset**\n[[Micro]](https:\/\/www.openml.org\/d\/44277) [[Mini]](https:\/\/www.openml.org\/d\/44307) ", "format": "arff", "uploader": "Amber ", "uploader_id": 30980, "visibility": "public", "creator": "\"Ihsan Ullah\"", "contributor": null, "date": "2022-11-08 19:00:09", "update_comment": null, "last_update": "2022-11-08 19:00:09", "licence": "CC BY-NC 4.0", "status": "active", "error_message": null, "url": "https:\/\/api.openml.org\/data\/download\/22111055\/dataset", "default_target_attribute": "CATEGORY", "row_id_attribute": null, "ignore_attribute": null, "runs": 0, "suggest": { "input": [ "Meta_Album_RSD_Extended", "## **Meta-Album RSD Dataset (Extended)** RSD46 dataset (https:\/\/github.com\/RSIA-LIESMARS-WHU\/RSD46-WHU) is collected from Google Earth and Tianditu. The collection contains 46 scene categories, with a total of 117 000 images. Each scene category has between 500 - 3000 images. The original resolution are 256x256 px or 512x512 px. We have created preprocessed version of RSD for Meta-Album by resizing the original dataset to 128x128 px. ### **Dataset Details** ![](https:\/\/meta-album.github.io\/asset " ], "weight": 5 }, "qualities": { "NumberOfInstances": 43825, "NumberOfFeatures": 3, "NumberOfClasses": 43, "NumberOfMissingValues": 43825, "NumberOfInstancesWithMissingValues": 43825, "NumberOfNumericFeatures": 1, "NumberOfSymbolicFeatures": 0, "PercentageOfSymbolicFeatures": 0, "AutoCorrelation": 1, "PercentageOfNumericFeatures": 33.33333333333333, "PercentageOfMissingValues": 33.33333333333333, "PercentageOfInstancesWithMissingValues": 100, "PercentageOfBinaryFeatures": 0, "NumberOfBinaryFeatures": 0, "MinorityClassSize": 1, "MinorityClassPercentage": 0.0022818026240730175, "MajorityClassSize": 3130, "MajorityClassPercentage": 7.142042213348546, "Dimensionality": 6.845407872219053e-5 }, "tags": [ { "tag": "study_318", "uploader": "0" } ], "features": [ { "name": "CATEGORY", "index": "1", "type": "string", "distinct": "43", "missing": "0", "target": "1" }, { "name": "FILE_NAME", "index": "0", "type": "string", "distinct": "43825", "missing": "0" }, { "name": "SUPER_CATEGORY", "index": "2", "type": "numeric", "distinct": "0", "missing": "43825", "min": "2147483647", "max": "0", "mean": "0", "stdev": "0" } ], "nr_of_issues": 0, "nr_of_downvotes": 0, "nr_of_likes": 0, "nr_of_downloads": 0, "total_downloads": 0, "reach": 0, "reuse": 0, "impact_of_reuse": 0, "reach_of_reuse": 0, "impact": 0 }