Ideal Regularized Kernel Subspace Alignment for Unsupervised Domain Adaptation in Hyperspectral Image Classification

Wenqi Fan
Wenqi Fan
Tianhui Wei
Tianhui Wei

MultiTemp, pp. 1-4, 2019.

EI
Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

This paper proposes a novel unsupervised domain adaption (DA) method called ideal regularized kernel subspace alignment (IRKSA) for hyperspectral image (HSI) classification. It first uses nonlinear projection to map the original source and target data into kernel space, then incorporates source labels into the source and target kernels by...More

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