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Innovative Text Extraction Algorithm Based on TensorFlow

机译:基于Tensorflow的创新文本提取算法

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Extracting business registration information exploiting graphic recognition algorithms on the Internet nowadays is vital to e-commercial business. However, business registration information is usually presented in graphics and existing graphic recognition systems have been hindered because of their slow detection speed, low accuracy, and complex operations. Thereby, we propose an innovative text extraction algorithm based on TensorFlow (TEAT). We first utilize the web crawler to obtain the data source, and then extract the character information by using our TEAT based on TensorFlow framework recognition technology. Our TEAT algorithm can extract business registration information efficiently and effectively. Comparing with existing text extraction algorithm based on Tess4j framework for extracting Tmall shop business license picture information, our TEAT has obvious advantages over Tess4j framework with higher accuracy and efficiency.
机译:提取商业登记信息现在在互联网上利用图形识别算法对电子商务业务至关重要。但是,商业注册信息通常以图形呈现,并且由于其检测速度,低精度和复杂操作慢,因此已经阻碍了现有的图形识别系统。由此,我们提出了一种基于Tensorflow(乳头)的创新文本提取算法。我们首先利用Web爬网程序获取数据源,然后通过基于Tensorflow框架识别技术使用我们的次来提取字符信息。我们的乳头算法可以有效且有效地提取商业登记信息。与基于TESS4J框架的现有文本提取算法进行比较,用于提取TMALL商店业务许可证信息,我们的乳头在TESS4J框架中具有明显的优点,具有更高的准确性和效率。

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