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## Meta-Album Insects2 Dataset (Extended) * The pest insects dataset was originally created as a large scale benchmark dataset for Insect Pest Recognition ( It contains more than 75 000 images belongs to 102 categories. It also has a hierarchical taxonomy and the insect pests which mainly affect one specific agricultural product are grouped into the same upper-level category. The preprocessed version is made from the original dataset by cropping the images in perfect squares and then resizing them into the required images size of 128x128. ### Dataset Details ![]( Meta Album ID: SM_AM.INS2 Meta Album URL: []( Domain ID: SM_AM Domain Name: Small Aninamls Dataset ID: INS_2 Dataset Name: Insects2 Short Description: Insects dataset for Insect Pest Recognition \# Classes: 102 \# Images: 75222 Keywords: insects, ecology Data Format: images Image size: 128x128 License (original data release): Free for academic usage, cite to use dataset License URL(original data release): License (Meta-Album data release): CC BY-NC 4.0 License URL (Meta-Album data release): []( Source: IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition Source URL: Original Author: Xiaoping Wu, Chi Zhan, Yukun Lai, Ming-Ming Cheng, Jufeng Yang Original contact: Meta Album author: Ihsan Ullah Created Date: 01 March 2022 Contact Name: Ihsan Ullah Contact Email: Contact URL: []( ### Cite this dataset ``` @inproceedings{Wu2019Insect, title={IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition}, author={Xiaoping Wu and Chi Zhan and Yukun Lai and Ming-Ming Cheng and Jufeng Yang}, booktitle={IEEE CVPR}, pages={8787--8796}, year={2019}, } ``` ### 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)string102 unique values
0 missing
FILE_NAMEstring75222 unique values
0 missing
SUPER_CATEGORYnumeric0 unique values
75222 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.
Number of attributes divided by the number of instances.
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
Percentage of nominal attributes.
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.
Percentage of binary attributes.
Percentage of instances having missing values.
Average class difference between consecutive instances.
Percentage of missing values.

1 tasks

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