基于原型约简融合的CBIR相关反馈

Samar Zutshi, Campbell Wilson, B. Srinivasan
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引用次数: 8

摘要

本文提出了两种相关的射频方法用于CBIR。这两种方法基于CBMR中射频的一般分类分析框架,该框架将射频独立于检索。所提出的方法显示了如何将用户的信息需求表示为一组“原型约简”,可以作为重新加权技术的基础,从而改善后续的检索。所提出的方法在两个具有不同特征的图像集合上进行了性能研究,并与现有的射频方法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Proto-reduct Fusion Based Relevance Feedback in CBIR
This paper proposes two related RF methods for use in CBIR. These two methods are based on a general classificatory analysis based framework for RF in CBMR that considers RF independently from retrieval. The proposed methods show how the user's information need expressed as a set of "proto-reducts'' can be used as the basis of a re-weighting technique that can improve subsequent retrieval The performance of the proposed methods is studied on two image collections with different characteristics and compared against an existing RF method.
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