论文利用图像自身的特性构造训练集合的源图像对，并学习他们之间的关系，达到图像分割的目的。

The property of input image is used to construct source image pair. We learn the relationship between source image pair, and then, use it for segmentation.

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只有当一个新的待抽取实例中的数据不能够被正确抽取时，系统再对其进行标注，因此算法无需初始的训练集合。

Only when a new instance cannot be extracted does it need labeling. So it does not require an initial set of labeled pages to learn extraction rules.

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结论该方法具有较高的准确性，在保证对训练集合90%以上的识别率的情况下，对测试集合的识别率达到80%以上。

This method proved to be highly accurate in predicting the tumor-specific promoters, with recognition rates of over 90% of the training sequences and over 80% of the testing sequences.

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