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matlab编程，基于颜色和纹理的图像检索算法的研究，思路清晰，方法有效。,matlab programming, based on the color and texture image retrieval algorithm is clearly thought effective.
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The GIFT (the GNU Image-Finding Tool) is a Content Based Image Retrieval System (CBIRS: http://en.wikipedia.org/wiki/CBIR). It enables you to do Query By Example (QBE: http://en.wikipedia.org/wiki/QBE) on images, giving you the opportunity to improve
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该代码为基于内容的图像检索系统CBIR中相关反馈的代码，相关反馈可以提高检索的查全查准率-The code is content-based image retrieval system, relevance feedback CBIR in the code, relevance feedback can improve the retrieval recall precision
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Graph-Cut Transducers for Relevance Feedback in Content Based Image Retrieval, Relevance Feedback for Content-Based Image Retrieval Using Bayesian Network,CONTENT BASED IMAGE RETRIEVAL,Relevance Feedback,A survey of browsing models for content based
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Content-based medical image retrieval is now getting more and more attention in the
world, a feasible and efficient retrieving algorithm for clinical endoscopic images is urgently
required. Methods: Based on the study of single feature image retr
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论文《A Stochastic Approach to Image Retrieval Using Relevance Feedback and Particle Swarm Optimization》的代码-the code of <A Stochastic Approach to Image Retrieval Using Relevance Feedback and Particle Swarm Optimization>
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基于内容的图像检索 基于颜色、纹理、形状的图像检索
基于区域的图像检索
基于语义的图像检索
相关反馈
-Based on the content-based image retrieval based on color, texture, shape-based image retrieval region-based image retrieval based on semantic image retrieval relevance feedback
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Nowadays, Content-Based Image Retrieval (CBIR) is the
mainstay of image retrieval systems. To understand the query
semantics and users expectations so as to communicate faithful
results in terms of accuracy, Relevance Feedback (RF) was
incorp
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In the current decade, we are witnessing a great interest in Content Based Image Retrieval (CBIR) together with a wealth of promising technologies, paved for a large number of new mechanisms and systems. In terms of mechanisms, a strong trend towards
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Content based image retrieval with relevance feedback tree.
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Survey about CBIR using Relevance Feedback
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