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Fuzzy image retrieval system

Authors: A. Aguilera; A.R. Suber; L. Martinez; A. Subero; L.J. Tineo;

Fuzzy image retrieval system

Abstract

To address the emerging needs of applications that require access to and retrieval of multimedia objects, we are developing an intelligent image retrieval system called FIRS. In this paper, we concentrate on the retrieval subsystem and its support for content-based queries over image databases. Content-based retrieval techniques (statistics, probabilistic, vector-oriented and fuzzy) have been extensively studied for textual documents in the area of automatic information retrieval. This paper show the adaptation of the fuzzy retrieval technique, used by the textual data, in the images' context.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Average
Average
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