Semi-supervised fuzzy neighborhood preserving analysis for feature extraction in hyperspectral remote sensing images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
http://link.springer.com/content/pdf/10.1007/s00521-017-3279-y.pdf
Reference43 articles.
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2. Bruzzone L, Persello C (2009) A novel approach to the selection of spatially invariant features for the classification of hyperspectral images with improved generalization capability. IEEE Trans Geosci Remote Sens 47(9):3180–3191
3. Rodarmel C, Shan J (2002) Principal component analysis for hyperspectral image classification. Surv Land Inf Sci 62(2):115
4. Chen G, Qian S-E (2007) Dimensionality reduction of hyperspectral imagery using improved locally linear embedding. J Appl Remote Sens 1(1):013509–013510
5. Belkin M, Niyogi P (2001) Laplacian eigenmaps and spectral techniques for embedding and clustering. In: NIPS, pp 585–591
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