Geodesic Flow Kernel Support Vector Machine for Hyperspectral Image Classification by Unsupervised Subspace Feature Transfer

Geodesic Flow Kernel Support Vector Machine for Hyperspectral Image Classification by Unsupervised Subspace Feature Transfer

In order to deal with scenarios where the training data, used to deduce a model, and the validation data have different statistical distributions, we study the problem of transformed subspace feature transfer for domain adaptation (DA) in the context of hyperspectral image classification via a geode...

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Bibliographic Details
Main Authors: Alim Samat, Paolo Gamba, Jilili Abuduwaili, Sicong Liu, Zelang Miao
Format: Article
Language:English
Published: MDPI AG 2016-03-01
Series:Remote Sensing
Subjects:
transfer learning
domain adaptation
geodesic flow kernel support vector machine
randomized nonlinear principal component analysis
feature transfer
image classification
Online Access:http://www.mdpi.com/2072-4292/8/3/234

Internet

http://www.mdpi.com/2072-4292/8/3/234

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