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Bor-Chen Kuo;
Chia-Hao Pai;
Tian-Wei Sheu;
Guey-Shya Chen;
Graduate Sch. of Educ. Meas. & Stat., Nat. Taichung Teachers Coll., Taiwan
This paper appears in: Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
Issue Date: 20-24 Sept. 2004
On page(s):
2937
- 2940 vol.5
Print ISBN: 0-7803-8742-2
INSPEC Accession Number: 8292800
Digital Object Identifier: 10.1109/IGARSS.2004.1370310
Date of Current Version:
27 December 2004
A new hybrid algorithm based on bagging and random subspace methods is proposed for improving hyperspectral data classification problem. The effects of using original data and transformed data in bagging, random subspace and the proposed algorithm are also explored. Real data experiment result shows that the proposed method performs well in both original and NWFE feature spaces.
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