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- W2364971024 abstract "Neighborhood Preserving Embedding(NPE) algorithm is a sub-space learning method, which has the ability to preserve the local neighboring structure information of the date. In order to improve the recognition function of the NPE algorithm used in hyperspectral image classification, we proposed an improved Semi-supervised Neighborhood Preserving Embedding(SSNPE) algorithm. Firstly, the algorithm uses both the labeled samples and the unlabeled samples of the neighborhood to get the neighborhood embedding structure. Secondly, improve the classification feature of the samples through raising weight of the labeled neighboring samples. Finally, get the classification function through using k-nearest Neighboring(KNN) classifier to classify the data set. The experimental results on the Urban, Indian Pine data sets show that the classification rate of the proposed algorithm is improved by more than about 8.3%, 6.2% compared to other algorithms, respectively, and thus the recognition performance has been improved clearly." @default.
- W2364971024 created "2016-06-24" @default.
- W2364971024 creator A5003375213 @default.
- W2364971024 date "2014-01-01" @default.
- W2364971024 modified "2023-09-28" @default.
- W2364971024 title "An Improved Neighborhood Preserving Embedding Method Used in Hyperspectral Image Classification" @default.
- W2364971024 hasPublicationYear "2014" @default.
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