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Deep Knowledge Training and Heterogeneous CNN for Handwritten Chinese Text Recognition

It is well known that the handwritten Chinese text recognition is a difficult problem since there are a large number of classes. In order to solve this problem, we proposed a whole new framework for unconstrained handwritten Chinese text recognition. The core module of the framework is the heterogeneous CNN trained by deep knowledge. The experimental results showed that our proposed method could achieve much better performance than the state-of-the-art methods (96.28% vs. 91.39% of CR on CASIA test set). Moreover, since the proposed framework is general, it can also be applied to other time sequence problems, such as speech recognition and video analysis.