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Combining MPEG-7 based visual experts for reaching semantics
Date
2003-01-01
Author
Soysal, M
Alatan, Abdullah Aydın
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
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Semantic classification of images using low-level features is a challenging problem. Combining experts with different classifier structures, trained by MPEG-7 low-level color and texture descriptors is examined as a solution alternative. For combining different classifiers and features, two advanced decision mechanisms are proposed, one of which enjoys a significant classification performance improvement. Simulations are conducted on 8 different visual semantic classes, resulting in accuracy improvements between 3.5-6.5%, when they are compared with the best performance of single classifier systems.
Subject Keywords
Support vector machine
,
Product rule
,
Semantic classis
,
Median rule
,
Homogeneous texture
URI
https://hdl.handle.net/11511/56074
Journal
VISUAL CONTENT PROCESSING AND REPRESENTATION, PROCEEDINGS
Collections
Department of Electrical and Electronics Engineering, Article