Lian-Zhi Huo

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A semisupervised kernel deformation function including spatial similarity is proposed for the classification of remote sensing images. The method exploits the characteristic of these images, in which spatially nearby points are likely to belong to the same class. To fulfill this assumption, a kernel encoding both spatial and spectral proximity using(More)
Remote sensing images provide essential data source for monitoring the land cover and land change on the Earth with a fast revisiting period. To fully utilize the remote sensing data, supervised classification methods are good choices to convert the data to land cover types due to their good abilities. One of the great challenges is to effectively collect(More)
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