Description: 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 similarity : Mahalanobis distance, the Euclidean distance relevance feedback : machine learning methods, such as SVM. Neural network search and classification : two very similar samples from the small, although the two are similar to the samples may not be much distance Platform: |
Size: 160149 |
Author:耿上 |
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Description: 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 Platform: |
Size: 320768 |
Author:亮亮 |
Hits:
Description: 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 similarity : Mahalanobis distance, the Euclidean distance relevance feedback : machine learning methods, such as SVM. Neural network search and classification : two very similar samples from the small, although the two are similar to the samples may not be much distance Platform: |
Size: 159744 |
Author:耿上 |
Hits:
Description: 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 Platform: |
Size: 320512 |
Author:亮亮 |
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Description: 图像检索中用于相关反馈的MATLAB程序供大家参考（注：在MATLAB7.0中使用）-Image Retrieval Relevance Feedback for the MATLAB program for your reference (Note: the use of MATLAB7.0) Platform: |
Size: 48128 |
Author:kitty |
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Description: 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 query results by relevance feedback. For processing your queries the program relies entirely on the content of the images, freeing you from the need to annotate all images before querying the collection. Platform: |
Size: 793600 |
Author:yudaxia |
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Description: 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 image retrieval,Analysis of Relevance Feedback in Content Based Image Retrieval, Performance Evaluation in Content-Based Image Retrieval: Overview and Proposals, COMPARISON OF TECHNIQUES FOR CONTENT-BASED IMAGE RETRIEVAL Platform: |
Size: 3459072 |
Author:sunda |
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Description: 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 features, based on the KDE paper: long-term cross-session relevance feedback in image retrieval Platform: |
Size: 622592 |
Author:冯立男 |
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Description: 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 retrieving techniques, including color
clustering, color texture and shape, a new retrieving method with multi-features fusion and relevance
feedback is proposed to retrieve the desired endoscopic images. Results: A prototype system is set
up to evaluate the proposed method’s performance and some evaluating parameters such as the
retrieval precision & recall, statistical average position of top 5 most similar image on various features, etc.
are therefore given. Conclusions: The algorithm with multi-features fusion and relevance feedback
gets more accurate and quicker retrieving capability than the one with single feature image retrieving
technique due to its flexible feature combination and interactive relevance feedback. Platform: |
Size: 359424 |
Author:gokul/goks |
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Description: 基于图像检索的matlab代码，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 similarity : Mahalanobis distance, the Euclidean distance relevance feedback : machine learning methods, such as SVM. Neural network search and classification : two very similar samples from the small, although the two are similar to the samples may not be much distance Platform: |
Size: 164864 |
Author:EmilyFu |
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Description: Based on the analysis of methods of CBIR and
chest image characteristic, in this paper, color
correlogam, dominant color of partition, gray level
co-occurrence matrix, gray-gradient co-occurrence
matrix and shape invariant moments were extracted as
retrieval feature. After comparison of their retrievals,
feature fusion and relevance feedback is proposed.
Experiments proved that the combining color, texture
with shape feature gets effective retrieval and relevance
feedback further more improves retrie Platform: |
Size: 900096 |
Author:Salkoum |
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Description: 图像检索相关反馈方面牛人的文章。很有参考价值。-The paper about the relevance feedback of Image retrieval . it is very useful. Platform: |
Size: 369664 |
Author:duyaqin |
Hits:
Search - Relevance Feedback Image Retrieval