Natural scene text recognition based on artificial intelligence machine learning

Jun Yin, Jianye Zhang, Degao Li
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引用次数: 0

Abstract

The text of physical scene images often contains a lot of accurate and advanced semantic information. Due to the rapid development of mobile networks and computer vision technology, this information has been widely used in applications such as geographic location, license plate identification, and unmanned driving. Therefore, this article mainly investigates the natural scene text recognition of artificial intelligence machine learning, and understands the relevant basic theories of natural scene text recognition on the basis of literature data, and then renews the natural scene text recognition using artificial intelligence machine learning, and test the quoted text recognition algorithm. The conclusion of the test is that the recognition accuracy of the algorithm in this paper is 83.7%, so the natural scene recognition model designed in this paper is effective.
基于人工智能机器学习的自然场景文本识别
物理场景图像的文本往往包含大量准确、高级的语义信息。由于移动网络和计算机视觉技术的快速发展,这些信息在地理定位、车牌识别、无人驾驶等应用中得到了广泛应用。因此,本文主要研究人工智能机器学习的自然场景文本识别,在文献数据的基础上了解自然场景文本识别的相关基本理论,然后利用人工智能机器学习更新自然场景文本识别,并对引用的文本识别算法进行测试。实验结果表明,本文算法的识别准确率为83.7%,表明本文设计的自然场景识别模型是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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