MNIST-MIX: a multi-language handwritten digit recognition dataset. (24th August 2020)

• Record Type: Journal Article
• Authors: Jiang, Weiwei
• Is Part Of: IOP SciNotes. Volume 1:Number 2(2020)
• Publication Date: 2020-08-24
• Subjects: deep learning -- handwritten digit recognition -- convolutional neural network; 500
• DOI: 10.1088/2633-1357/abad0e
• Languages: English
• ISSNs: 2633-1357

Abstract

Abstract: In this note, we contribute a multi-language handwritten digit recognition dataset named MNIST-MIX, which is the largest dataset of the same type in terms of both languages and data samples. With the same data format with MNIST, MNIST-MIX can be seamlessly applied in existing studies for handwritten digit recognition. By introducing digits from 10 different languages, MNIST-MIX becomes a more challenging dataset and its imbalanced classification requires a better design of models. We also present the results of applying a LeNet model which is pre-trained on MNIST as the baseline.