Combining MPEG-7 based visual experts for reaching semantics

2003-01-01
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.
VISUAL CONTENT PROCESSING AND REPRESENTATION, PROCEEDINGS

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Citation Formats
M. Soysal and A. A. Alatan, “Combining MPEG-7 based visual experts for reaching semantics,” VISUAL CONTENT PROCESSING AND REPRESENTATION, PROCEEDINGS, pp. 66–75, 2003, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56074.