Visual concept detection by stacked generalization

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2014

Author

Tekin, Mashar

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In this thesis, we propose a new Stacked Generalization method, called Fuzzy Stacked Generalized Ranking Optimizer, to optimize the ranking performances of visual concept detection systems. In the proposed method, fuzzy k-NN classifiers are employed in the base-layer. Then, a classifier selection algorithm is employed to select the classifiers which will be combined in meta-layer. Finally, the results of the selected classifiers are combined and classified by a fuzzy k-NN meta classifier. In the experiments, the proposed method performs better than the state of the art ensemble learning methods.

Subject Keywords

Image processing., Image processing, Fuzzy algorithms., Cluster set theory.

URI

http://etd.lib.metu.edu.tr/upload/12617663/index.pdf
https://hdl.handle.net/11511/23765

Collections

Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

M. Tekin, “Visual concept detection by stacked generalization,” M.S. - Master of Science, Middle East Technical University, 2014.