TITLE: Afro-MNIST: Synthetic generation of MNIST-style datasets for low-resource languages 

ABSTRACT: We present Afro-MNIST, a set of synthetic MNIST-style datasets for four
orthographies used in Afro-Asiatic and Niger-Congo languages: Ge`ez (Ethiopic),
Vai, Osmanya, and N'Ko. These datasets serve as "drop-in" replacements for
MNIST. We also describe and open-source a method for synthetic MNIST-style
dataset generation from single examples of each digit. These datasets can be
found at https://github.com/Daniel-Wu/AfroMNIST. We hope that MNIST-style
datasets will be developed for other numeral systems, and that these datasets
vitalize machine learning education in underrepresented nations in the research
community.
We present Afro-MNIST, a set of synthetic MNIST-style datasets for four
orthographies used in Afro-Asiatic and Niger-Congo languages: Ge`ez (Ethiopic),
Vai, Osmanya, and N'Ko. These datasets serve as "drop-in" replacements for
MNIST. We also describe and open-source a method for synthetic MNIST-style
dataset generation from single examples of each digit. These datasets can be
found at https://github.com/Daniel-Wu/AfroMNIST. We hope that MNIST-style
datasets will be developed for other numeral systems, and that these datasets
vitalize machine learning education in underrepresented nations in the research
community.
Afro-MNIST: Synthetic generation of MNIST-style datasets for low-resource languages
http://arxiv.org/abs/2009.13509v1