Abstract
The paper describes a new relevance feedback mechanism that evaluates the distribution of the features of images judged relevant or not relevant by the user, and dynamically updates both the similarity measure and query in order to accurately represent the user’s particular information needs. Experimental results are reported to demonstrate the effectiveness of this mechanism.
Cite
CITATION STYLE
Ciocca, G., & Schettini, R. (1999). Using a relevance feedback mechanism to improve content-based image retrieval. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1614, pp. 107–114). Springer Verlag. https://doi.org/10.1007/3-540-48762-x_14
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