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基于内容的图像检索中的一些关键环节：特征提取：颜色直方图；纹理特征等
相似度：马氏距离，欧氏距离等
相关反馈：机器学习方法，如SVM，神经网络等
检索与分类：两个很相似的样本距离很小，虽然两个不相似的样本距离未必很大-content-based image retrieval of some of the key issues : Feature Extraction : color histogram; Texture characteristics of simila
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一种特征库可更新的相关反馈图像检索方法，写的比较详细做图像检索反馈时可以参考-a feature library can be updated relevance feedback image retrieval methods, write more detailed feedback so images can be indexed reference
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使用BDA实现三维模型相关反馈的算法
注：1、使用本系统必须在本地计算机上安装matlab
2、算法使用的三维模型特征向量是从PSB模型库中自动提取的DESIRE三维模型特征向量
3、本系统自带性能评测机制-use 3D model relevance feedback algorithm Note : 1. Use of this system must be installed on the local computer Matlab 2, algorithm using 3D
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使用KernelBDA实现三维模型相关反馈的算法注：1、使用本系统必须在本地计算机上安装matlab
2、算法使用的三维模型特征向量是从PSB模型库中自动提取的DESIRE三维模型特征向量 3、本系统自带性能评测机制-KernelBDA use 3D model relevance feedback algorithm Note : 1. Use of this system must be installed on the local computer Matlab 2, algorit
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使用LDA实现三维模型相关反馈的算法注：1、使用本系统必须在本地计算机上安装matlab 2、算法使用的三维模型特征向量是从PSB模型库中自动提取的DESIRE三维模型特征向量 3、本系统自带评测机制-use 3D model relevance feedback algorithm Note : 1. Use of this system must be installed on the local computer Matlab 2, algorithm using 3D model fro
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使用BDA实现三维模型相关反馈的算法
注：算法使用的三维模型特征向量是从PSB模型库中自动提取的DESIRE三维模型特征向量 -use 3D model relevance feedback algorithm Note : algorithm using 3D model from the eigenvectors of the PSB model automatically from the 3D model features DESIRE to volume
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一种基于svm相关反馈的图象检索算法-svm based relevance feedback algorithm for image retrieval
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一个基于内容的图像检索程序，用于相关反馈检索，采用自己研制（已发表）的查询点学习算法。-a content-based image retrieval procedure for relevance feedback retrieval, own research (published) inquiries point learning algorithm.
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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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本文提出了一种在获取图像低层视觉特征的基础上，利用语义网络对
图像进行语义自动分类，并在此基础上引入相关反馈技术，使图像的低级
物理特征和高级语义特征联系起来的算法，通过人一机协同工作，来弥补
计算机理解能力的不足，不断提高检索效果。
-In this paper, a low-level access to images based on visual characteristics, the use of semantic networks semantic image au
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基于支持向量机的相关反馈图像检索算法
相关反馈技术是近年来在图像检索中较为重要的
研究方法, 从机器学习的角度, 以支持向量机(SVM ) 为分类器, 提出了一种新的相关反馈方法-Support vector mach ine based relevance
feedback algorithm in image retrieval
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The first scheme is based on the spatial locality of feature vectors corresponding
to similar images. Learning is effected by modifying the query vector to incorporate the
positive examples. The second scheme is based on “distorting” our view of
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个人代码，实现了基于内容的图像检索，包括relevance feedback, virtual feature等特性,基于KDE paper: long-term cross-session relevance feedback in image retrieval-Personal code, to achieve a content-based image retrieval, including relevance feedback, virtual feature and other f
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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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查询行为和关联规则的相关反馈查询扩Behavior and association rule -Behavior and association rule query relevance feedback query expansion
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Summary presentation of the relevance feedback algorithms for information retrieval
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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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粒子群优化算法及其在图像检索中相关反馈上的应用-Particle Swarm Optimization and its relevance feedback in image retrieval
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