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.

中文翻译：

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MNIST-MIX：多语言手写数字识别数据集

在此注释中，我们贡献了一个名为MNIST-MIX的多语言手写数字识别数据集，这是就语言和数据样本而言，相同类型的最大数据集。利用与MNIST相同的数据格式，MNIST-MIX可以无缝应用于现有研究中以进行手写数字识别。通过引入10种不同语言的数字，MNIST-MIX成为更具挑战性的数据集，其不平衡分类要求对模型进行更好的设计。我们还介绍了应用LeNet模型的结果，该模型在MNIST作为基线进行了预训练。