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Extracting essential features from massive bands is an important yet challenging issue in hyperspectral image (HSI) classification. Plenty of feature extraction techniques can be found in the literature but most of these methods rely on linear/stationary assumptions. This paper proposes an alternative methodology inspired by the ensemble empirical mode decomposition (EEMD) to gain spectral features...
The mathematical modeling of classifier has been intensively investigated in pattern recognition for decades. Maximin classifier, which conducts optimization based on the perpendicularly closest data point(s) to the decision boundary, has been widely used. However, such method may lead to inferior performance when the boundary data point(s) is significantly influenced by noise. This paper presents...
This paper proposes a feature relation network (FRN) to model the underlying feature relation structures of a set of observations. A pattern classification system is then constructed based on the feature relation network, namely PCS-FRN. During training process, PCS-FRN will form an attractor for each group of samples in order to lower the overall energy states. The attractor, or a feature relation...
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