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Nonlinear classifier combination for simple combination types

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2 Author(s)
Sen, M.U. ; Sabanci Univ., Istanbul, Turkey ; Erdogan, H.

Classifier combination has been an important research area because of their contribution to the accuracy and robustness. Supervised linear combiner types are shown to be strong combiners; but nonlinear types are not well investigated. In this work, we show a method to obtain non-linear versions of simple linear combiner types. Experiments are conducted on four different databases and results are examined. It is observed that we can obtain better accuracies with non-linear combinations for certain types.

Published in:

Signal Processing and Communications Applications (SIU), 2011 IEEE 19th Conference on

Date of Conference:

20-22 April 2011