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The HMM-based segmentation-free strategy for Chinese handwriting recognition has the advantage of training without annotation of character boundaries. However, the recognition performance has been limited by the small number of string samples. In this paper, we explore two techniques to improve the performance. First, Delta features are added to the static ones for alleviating the conditional independence...
Directional features are preferred in off-line Chinese character recognition due to their superior performance. This paper proposes an enhanced four plane feature (en-FPF) within a segmentation-free recognition framework. First, the directional planes are strengthened by replenishing salient pixels. Second, the method to count perpendicular strokes are renewed. In experiments of realistic Chinese...
A segmentation-free strategy based on hidden Markov models (HMMs) is presented for offline recognition of unconstrained Chinese handwriting. As the first step, handwritten textlines are converted to observation sequence by sliding windows and character segmentation stage is avoided prior to recognition. Following that, embedded Baum-Welch algorithm is adopted to train character HMMs. Finally, best...
Automatic tools to extract information from biomedical texts are needed to help researchers leverage the vast and increasing body of biomedical literature. While several biomedical relation extraction systems have been created and tested, little work has been done to meaningfully organize the extracted relations. Organizational processes should consolidate multiple references to the same objects over...
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