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Omniglot dataset

The Omniglot dataset consists of 100 classes, each containing 20 images. Ten images were taken from each class for augmentation, and the rest were used as the test set. Each image can generate 2004 new images by the ND-MLS method, so 2 million images were used for the training model.

Data and Resources

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Cite this as

Arman Kazemi, Mohammad Mehdi Shari, Ann Franchesca Laguna, Franz M¨uller, Ramin Rajaei, Ricardo Olivo, Thomas K¨ampfe, Michael Niemier, X. Sharon Hu (2024). Dataset: Omniglot dataset. https://doi.org/10.57702/jp2k7lbz

DOI retrieved: December 2, 2024

Additional Info

Field Value
Created December 2, 2024
Last update December 2, 2024
Defined In https://doi.org/10.48550/arXiv.2011.07095
Citation
  • https://doi.org/10.48550/arXiv.1711.02679
  • https://doi.org/10.48550/arXiv.2005.08482
  • https://doi.org/10.48550/arXiv.2103.00694
Author Arman Kazemi
More Authors
Mohammad Mehdi Shari
Ann Franchesca Laguna
Franz M¨uller
Ramin Rajaei
Ricardo Olivo
Thomas K¨ampfe
Michael Niemier
X. Sharon Hu
Homepage https://www.omniglot.com/omniglot/datasets.html