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The semantic web and computer vision: old AI meets new AI

机译:语义网和计算机视觉:旧AI与新AI相遇

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There has been vast process in linking semantic information across the billions of web pages through the use of ontologies encoded in the Web Ontology Language (OWL) based on the Resource Description Framework (RDF). A prime example is the Wikipedia where the knowledge contained in its more than four million pages is encoded in an ontological database called DBPedia http://wiki.dbpedia.org/. Web-based query tools can retrieve semantic information from DBPedia encoded in interlinked ontologies that can be accessed using natural language. This paper will show how this vast context can be used to automate the process of querying images and other geospatial data in support of report changes in structures and activities. Computer vision algorithms are selected and provided with context based on natural language requests for monitoring and analysis. The resulting reports provide semantically linked observations from images and 3D surface models.
机译:通过使用基于资源描述框架(RDF)的Web本体语言(OWL)中编码的本体,跨数十亿个网页链接语义信息的过程已经很广泛。一个典型的例子是Wikipedia,其中超过四百万页中包含的知识被编码在称为DBPedia http://wiki.dbpedia.org/的本体数据库中。基于Web的查询工具可以从DBPedia中检索以互连本体编码的语义信息,可以使用自然语言进行访问。本文将展示如何利用这种广阔的背景来自动化查询图像和其他地理空间数据的过程,以支持结构和活动的报告更改。选择计算机视觉算法并根据自然语言请求提供上下文,以进行监控和分析。生成的报告提供了来自图像和3D表面模型的语义链接的观察结果。

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