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## Meta-Album Airplanes Dataset (Extended) * The original Airplanes dataset ( comprises more than 9 000 remote sensing images acquired from Google Earth satellite imagery, including 21 different types of aircraft from around 36 airports. All the images were carefully labeled by seven specialists in the field of remote sensing image interpretation. Each class can have 230 to 846 images, where each image contains only one complete aircraft, and they have variable resolutions. To preprocess this dataset, we cropped the images from either side to make them square, and then we resized them into 128x128 px using an anti-aliasing filter. ### Dataset Details ![]( Meta Album ID: VCL.APL Meta Album URL: []( Domain ID: VCL Domain Name: Vehicles Dataset ID: APL Dataset Name: Airplanes Short Description: Airplanes dataset with different aiplane models \# Classes: 21 \# Images: 9625 Keywords: vehicles, airplanes Data Format: images Image size: 128x128 License (original data release): Creative Commons Attribution 4.0 International License URL(original data release): License (Meta-Album data release): Creative Commons Attribution 4.0 International License URL (Meta-Album data release): []( Source: Muti-type Aircraft of Remote Sensing Images: MTARSI Source URL: Original Author: Wu, Zhize Original contact: Meta Album author: Philip Boser Created Date: 01 March 2022 Contact Name: Ihsan Ullah Contact Email: Contact URL: []( ### Cite this dataset ``` @dataset{wu_zhize_2019_3464319, author = {Wu, Zhize}, title = {{Muti-type Aircraft of Remote Sensing Images: MTARSI}}, month = may, year = 2019, publisher = {Zenodo}, doi = {10.5281/zenodo.3464319}, url = {} } ``` ### 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 = {}, year = {2022} } ``` ### More For more information on the Meta-Album dataset, please see the [[NeurIPS 2022 paper]]( For details on the dataset preprocessing, please see the [[supplementary materials]]( Supporting code can be found on our [[GitHub repo]]( Meta-Album on Papers with Code [[Meta-Album]]( ### Other versions of this dataset [[Micro]]( [[Mini]](

3 features

CATEGORY (target)string21 unique values
0 missing
FILE_NAMEstring9625 unique values
0 missing
SUPER_CATEGORYnumeric0 unique values
9625 missing

19 properties

Number of instances (rows) of the dataset.
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
Number of missing values in the dataset.
Number of instances with at least one value missing.
Number of numeric attributes.
Number of nominal attributes.
Percentage of binary attributes.
Percentage of instances having missing values.
Percentage of missing values.
Average class difference between consecutive instances.
Percentage of numeric attributes.
Number of attributes divided by the number of instances.
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
Number of binary attributes.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: CATEGORY
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