New proposition for intelligent systems design: artificial understanding of the images as the next step of advanced data analysis after automatic classification and pattern recognition

R. Tadeusiewicz, M. Ogiela
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引用次数: 16

Abstract

In this paper there will be presented the new opportunities for applying linguistic algorithms of pattern recognition for computer understanding of image semantic content in intelligent information systems. A successful obtaining of the crucial semantic information of the image - especially medical - may contribute considerably to the creation of new intelligent cognitive information systems. Thanks to the new algorithms of cognitive resonance between stream of the data extracted from the image and expectations taken from the representation of the medical knowledge, we can understand the merit content of the image even if the form of the image is very different from any known pattern. It seems that in the near future the technique of automatic understanding of images may become one of the effective tools for semantic interpreting, and intelligent storing of the visual data in scattered databases. In this article we will try proving that structural techniques may be applied in the case of tasks related to automatic classification and machine perception of the semantic meaning of selected classes of medical patterns.
智能系统设计的新命题:人工理解图像作为自动分类和模式识别之后的高级数据分析的下一步
本文将介绍在智能信息系统中应用模式识别语言算法对图像语义内容进行计算机理解的新机会。成功获取图像的关键语义信息——尤其是医学信息——可能对创建新的智能认知信息系统有很大贡献。由于从图像中提取的数据流与从医学知识表示中获得的期望之间的认知共振的新算法,即使图像的形式与任何已知模式都有很大不同,我们也可以理解图像的优点内容。在不久的将来,图像自动理解技术可能成为语义解释和可视化数据智能存储的有效工具之一。在本文中,我们将尝试证明结构技术可以应用于与自动分类和机器感知选定类别的医学模式语义相关的任务中。
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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