Kuzushiji-MNIST is a new alternative dataset for the well-known MNIST. The new dataset can serve as a new benchmark system for classification algorithms and can help restoring millions of books from the almost lost Japanese language - Kuzushiji.
The paper describes the dataset, its extraction process and a few use cases and results.
A summary of the paper can be found here.
This code achieves state-of-the-art results (98.9%) on Kuzushiji-MNIST using an ensemble of VGG Network and ResNet and implemented with PyTorch and FastAI (v1).
It also provides a Kuzushiji-MNIST Dataset class to help others use the new dataset.
