Hyperspectral Data Classification Using Nonparametric Weighted Feature Extraction. Bor-Chen Kuo, Member, IEEE. Department of Mathematic Education. National ...
In this paper, a new nonparametric feature extraction method is proposed for high dimensional multiclass pattern recognition problems.
In this paper, a new nonparametric feature extraction method is proposed for high dimensional multiclass pattern recognition problems.
In this paper, a new nonparametric linear feature extraction method is introduced for classification of hyperspectral images. The proposed method has no free ...
Jan 13, 2024 · In this paper, a new nonparametric feature extraction method is proposed for high-dimensional multiclass pattern recognition problems.
We propose the optimized kernel non-parametric weighted feature extraction for hyperspectral image classification. KNWFE is a kernel-based feature extraction ...
Some studies show that nonparametric weighted feature extraction (NWFE; Kuo and Landgrebe, 2004) is a powerful tool to extract hyperspectral image features for ...
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What is feature extraction in hyperspectral data?
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We propose the optimized kernel non-parametric weighted feature extraction for hyperspectral image classification. KNWFE is a kernel-based feature extraction ...
Feature extraction plays a crucial role in improvement of hyperspectral images classification. Nonparametric feature ... weight in the within-class scatter matrix ...
Many researches show that nonparametric weighted feature extraction (NWFE) is a powerful tool for extracting hyperspectral image features and kernel-based ...