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Semi-incremental Recognition of Online Handwritten Mathematical Expressions

机译:在线手写数学表达的半增量式识别

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This paper presents a semi-incremental recognition method for online handwritten mathematical expressions (MEs). The method reduces the waiting time after an ME is written until the result of recognition is output. Our method has two main processes, one is to process the latest stroke, the other is to find and correct wrong recognitions in the strokes up to the latest stroke. In the first process, the segmentation, recognition and Cocke-Younger-Kasami (CYK) algorithm are only executed for the latest stroke. In the second process, all the previous segmentations are updated if they are significantly changed after the latest stroke is input, and then, all the symbols related to the updated segmentations will be updated with their recognition scores. These changes are reflected into the CYK table. In addition, the waiting time is further reduced by employing multi-thread processes. Experiments on our data set show the effectiveness of this semi-incremental method which not only has higher recognition rate than our previous pure-incremental method but also keeps the waiting time unnoticeable.
机译:本文提出了一种用于在线手写数学表达式(ME)的半增量识别方法。该方法减少了在写入ME之后直到输出识别结果的等待时间。我们的方法有两个主要过程,一个是处理最新笔画,另一个是找到并纠正笔画中直到最新笔画的错误识别。在第一个过程中,仅对最新笔划执行分割,识别和Cocke-Younger-Kasami(CYK)算法。在第二过程中,如果在输入最新笔划之后对所有先前的分段进行了显着更改,则将更新所有先前的分段,然后,将使用其识别分数来更新与更新的分段相关的所有符号。这些更改反映在CYK表中。另外,通过采用多线程进程,可以进一步减少等待时间。在我们的数据集上进行的实验表明,这种半增量方法的有效性不仅比我们以前的纯增量方法具有更高的识别率,而且还使等待时间不明显。

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