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Content Based Image Retrieval Using Adaptive Inverse Pyramid Representation

机译:基于自适应逆金字塔表示的基于内容的图像检索

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This paper presents a new approach for content-based image retrieval using cognitive representation with pyramidal decomposition. This approach corresponds to the hypothesis of the human way for object recognition based on consecutive approximations with increased resolution for the selected regions of interest. The method is based on object model creation with Inverse Difference Pyramid controlled by neural network. The method's basic advantages are the high flexibility and the ability to create general models for various views and scaling with relatively low computational complexity. The method is suitable for great number of applications - medicine, digital libraries, electronic galleries, geographic information systems, documents archiving, digital communication systems, etc.
机译:本文提出了一种新的基于金字塔分解的认知表示的基于内容的图像检索方法。该方法对应于基于连续的逼近,针对选定的感兴趣区域具有更高分辨率的对象识别方法的人类假设。该方法基于具有神经网络控制的逆差金字塔的对象模型创建。该方法的基本优点是灵活性高,并且能够以相对较低的计算复杂性为各种视图和缩放比例创建通用模型。该方法适用于多种应用-医学,数字图书馆,电子画廊,地理信息系统,文档归档,数字通信系统等。

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