Boosting in Classifier Fusion vs. Fusing Boosted Classifiers
In this paper we investigate the performance of boosting used for fusing various classifiers. We propose a new boosting - based algorithm for fusion and we show through empirical studies on texture image data sets that it outperforms existing SVM-based classifier fusion technique in terms of accuracy, computational efficiency and robustness.
MSU Digital Commons Citation
Barbu, Costin; Zhang, Kun; Peng, Jing; and Buckles, Bill, "Boosting in Classifier Fusion vs. Fusing Boosted Classifiers" (2005). Department of Computer Science Faculty Scholarship and Creative Works. 150.