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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40563

Title: Applying Composite Kernel to Kernel-based Nonparametric Weighted Feature Extraction
Authors: Chih-Sheng Huang;Cheng-Hsuan Li;Shih-Syun Lin;Bor-chen Kuo
Contributors: 國立臺灣海洋大學:資訊工程學系
Date: 2010
Issue Date: 2017-01-20T02:25:44Z
Publisher: Industrial Electronics and Applications (ICIEA), 2010 the 5th IEEE Conference on
Abstract: Abstract: In the recent researches show that nonparametric weighted feature extraction (NWFE) is a useful method for extracting hyperspectral image features. Kernel-based NWFE (KNWFE) is applying the kernel method to extend the more effective projected features in the feature space. It had been showed the performance of KNWFE is better than NWFE. In this study, we would apply a composite kernel function with spectral and spatial information to KNWFE, and hope this composite kernel to KNWFE can get a better performance than the spectral-based kernel function to KNWFE. In the experiment results show that the KNWFE with composite kernel, include the spectral and spatial information, outperforms the KNWFE with the only spectral based kernel function.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40563
Appears in Collections:[資訊工程學系] 演講及研討會

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