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In this digital world, there is a large requirement of high resolution satellite image. Images at a low resolution may contain relevant information that has to be integrated with the high resolution i...
Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for Hyperspectral Image Classification. The manifold learnin...
Abstract: It has recently been shown that an unbinned distance-based statistic, the energy, can be used to construct an extremely powerful nonparametric multivariate two sample goodness-of-fit test. A...
We describe dimensionally constrained symbolic regression which has been developed for mass measurement in certain classes of events in high-energy physics (HEP).With symbolic regression, we can deriv...
Forest canopies reduce shortwave radiation and increase longwave radiation reaching the underlying surface, compared with open areas, and thus influence rates at which forest snowpacks melt. Th...
2005Vol.43No.1pp.102-106DOI: Phase Space Prediction of Chaotic Time Series with Nu-Support Vector Machine Regression YE Mei-Ying1 and WANG Xiao-Dong2 1 College of Mathem...

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