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In-air handwriting is becoming a new human-computer interaction way. It is a challenging task to accurately recognizing in-air handwritten Chinese characters. In this paper, we present an end-to-end recognizer for in-air handwritten Chinese characters by using recurrent neural networks (RNN). Compared with the existing methods, the proposed RNN based methods does not need to explicitly extract features...
Dimensionality reduction methods have been shown to be effective for handwritten Chinese character recognition. In this paper, we propose discriminative projection based on locality-sensitive sparse representation (DPLSR) for in-air handwritten Chinese character recognition. DPLSR based on the locality-sensitive sparse representation based classifier (LSRC), which can provide closed-form solutions...
The in-air handwriting is a natural and promising humancomputer interaction way. Compared with handwritten Chinese characters on touch screen, the in-air handwritten Chinese characters have their unique characteristics, e.g., each character is always written in a single stroke. In this paper, we propose a high-order directional feature for recognizing in-air handwritten Chinese characters. The proposed...
Discriminative locality alignment (DLA) has been successfully applied in similar handwritten Chinese character recognition (SHCCR). But, the performance of DLA heavily depends on the choice of parameters and the optimal parameters among different groups of similar characters are not consistent. To address this problem, we present an improved method with few parameters, called adaptive discriminative...
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