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Feature aggregation is a critical technique in contentbased image retrieval systems that employ multiple visual features to characterize image content. In this paper, the p-norm is introduced to feature aggregation that provides a framework to unify various previous feature aggregation schemes such as linear combination, Euclidean distance, Boolean logic and decision fusion schemes in which previous schemes are instances. Some insights of the mechanism of how various aggregation schemes workdoi:10.1109/ism.2007.4412374 dblp:conf/ism/ZhangY07 fatcat:uxvyune3jjd7hcefswb6opqz6i