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Proceedings Paper

Evaluation of feature measures and similarity measures for content-based retrieval
Author(s): Jiankang Wu; Chianprong Lam; G. Senthilkumar
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Paper Abstract

Evaluation is a critical issue in any information systems. This problem has become more and more important with the rapid development of multimedia systems. Feature measures and similarity measures play a central role in content-based retrieval. Evaluation of their effectiveness and efficiency then become a key issue in assessing the performance of a content- based multimedia system. A learning algorithm has been studied to find a suitable and hopefully the best similarity function for a given set of feature measure and a given set of training data set.

Paper Details

Date Published: 21 November 1995
PDF: 11 pages
Proc. SPIE 2606, Digital Image Storage and Archiving Systems, (21 November 1995); doi: 10.1117/12.227248
Show Author Affiliations
Jiankang Wu, National Univ. of Singapore (Singapore)
Chianprong Lam, National Univ. of Singapore (Singapore)
G. Senthilkumar, National Univ. of Singapore (Singapore)


Published in SPIE Proceedings Vol. 2606:
Digital Image Storage and Archiving Systems
C.-C. Jay Kuo, Editor(s)

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