Chibelushi, C.C. and Deravi, F. and Mason, J.S.D. (1999) Adaptive classifier integration for robust pattern recognition. Ieee Transactions on Systems Man and Cybernetics Part B-Cybernetics, 29 (6). pp. 902-907. ISSN 1083-4419.
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| Official URL http://dx.doi.org/10.1109/3477.809043 |
Abstract
The integration of multiple classifiers promises higher classification accuracy and robustness than can be obtained with a single classifier. This paper proposes a ne rv adaptive technique for classifier integration based on a linear combination model. The proposed technique is shown to exhibit robustness to a mismatch between test and training conditions. It often outperforms the most accurate of the fused information sources. A comparison between adaptive linear combination and non-adaptive Bayesian fusion shows that, under mismatched test and training conditions, the former is superior to the latter in terms of identification accuracy and insensitivity to information source distortion.
| Item Type: | Article |
|---|---|
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts |
| Depositing User: | M. Nasiriavanaki |
| Date Deposited: | 26 Jun 2009 07:32 |
| Last Modified: | 26 Jun 2009 07:32 |
| Resource URI: | http://kar.kent.ac.uk/id/eprint/17206 (The current URI for this page, for reference purposes) |
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