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- W2016097963 abstract "Hyperspectral remote sensing is a technique based on the spectroscopy, which contains abundant spectral information besides the spatial information of the images, and overcomes the limitations of the wide-band remote sensing detection. When classifying hyperspectral and multispectral images with the existing algorithms, we use only the spectral information more often. This paper presents an one-class classification techniques, which is based spatial-contextual term, this study modifies the decision function and constraints of support vector data description. Experimental results show that the proposed method achieves good classification performance on hyperspectral image." @default.
- W2016097963 created "2016-06-24" @default.
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- W2016097963 date "2013-07-01" @default.
- W2016097963 modified "2023-10-18" @default.
- W2016097963 title "A one-class classification by spatial-contextual for remotely sensed image" @default.
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- W2016097963 doi "https://doi.org/10.1109/igarss.2013.6721186" @default.
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