首页> 外国专利> Relevance maximizing, iteration minimizing, relevance-feedback, content-based image retrieval (CBIR).

Relevance maximizing, iteration minimizing, relevance-feedback, content-based image retrieval (CBIR).

机译:相关性最大化,最小化迭代,相关性反馈,基于内容的图像检索(CBIR)。

摘要

An implementation of a technology, described herein, for relevance-feedback, content-based facilitating accurate and efficient image retrieval minimizes the number of iterations for user feedback regarding the semantic relevance of exemplary images while maximizing the resulting relevance of each iteration. One technique for accomplishing this is to use a Bayesian classifier to treat positive and negative feedback examples with different strategies. In addition, query refinement techniques are applied to pinpoint the users' intended queries with respect to their feedbacks. These techniques further enhance the accuracy and usability of relevance feedback. This abstract itself is not intended to limit the scope of this patent. The scope of the present invention is pointed out in the appending claims.
机译:本文描述的用于基于内容的相关性反馈的技术的实现方式,其促进准确和有效的图像检索,从而使关于示例图像的语义相关性的用户反馈的迭代次数最小化,同时使每个迭代的结果相关性最大化。实现此目的的一种技术是使用贝叶斯分类器以不同的策略处理正反馈示例和负反馈示例。另外,查询细化技术被应用于针对用户的反馈查明用户的预期查询。这些技术进一步提高了相关性反馈的准确性和可用性。该摘要本身并不旨在限制本专利的范围。在所附权利要求中指出了本发明的范围。

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