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Case Study: MUSE

  • Oge Marques
  • Borko Furht
Part of the Multimedia Systems and Applications Series book series (MMSA, volume 21)

Abstract

In this chapter we present MUSE (MUltimedia SEarch and Retrieval Using Relevance Feedback), a CBVIR system with relevance feedback and learning capabilities developed by the authors over the past two years. MUSE is an ongoing project within the Department of Computer Science and Engineering at Florida Atlantic University. The ultimate goal of this project is to build an intelligent system for searching and retrieving visual information in large repositories1.

Keywords

Feature Vector Cluster Algorithm Target Image Query Image Relevance Feedback 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Oge Marques
    • 1
  • Borko Furht
    • 1
  1. 1.Florida Atlantic UniversityBoca RatonUSA

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