The documents of the government-general of Taiwan recorded from 1895 to 1945 contain the whole of Japanese official documents before the end of the WW2, and have great historic value. The characters in the documents, however, are illegible because they were written by hand with a brush. It is labor-intensive work for historians or scholars to understand the documents. We propose a method for character recognition of these documents by using a convolutional neural network and also conduct to solve the problem of imbalanced learning data. Experimental results show that the top-1 and the top10 accuracies were 89.48% and 98.10%, respectively.
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