Abstract
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.
Original language | English |
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Title of host publication | Proceedings of the 2005 IEEE International Conference on Information Reuse and Integration, IRI - 2005 |
Pages | 332-337 |
Number of pages | 6 |
Volume | 2005 |
DOIs | |
State | Published - 1 Dec 2005 |
Event | 2005 IEEE International Conference on Information Reuse and Integration, IRI - 2005 - Las Vegas, NV, United States Duration: 15 Aug 2005 → 17 Aug 2005 |
Other
Other | 2005 IEEE International Conference on Information Reuse and Integration, IRI - 2005 |
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Country/Territory | United States |
City | Las Vegas, NV |
Period | 15/08/05 → 17/08/05 |