Empirical Inference
Article
2010
Spatio-Spectral Remote Sensing Image Classification With Graph Kernels
Web
Empirical Inference
Empirical Inference
This letter presents a graph kernel for spatio-spectral remote sensing image classification with support vector machines (SVMs). The method considers higher order relations in the neighborhood (beyond pairwise spatial relations) to iteratively compute a kernel matrix for SVM learning. The proposed kernel is easy to compute and constitutes a powerful alternative to existing approaches. The capabilities of the method are illustrated in several multi- and hyperspectral remote sensing images acquired over both urban and agricultural areas.
| Author(s): | Camps-Valls, G. and Shervashidze, N. and Borgwardt, K. |
| Links: | |
| Journal: | IEEE Geoscience and Remote Sensing Letters |
| Volume: | 7 |
| Number (issue): | 4 |
| Pages: | 741-745 |
| Year: | 2010 |
| Month: | October |
| Day: | 0 |
| BibTeX Type: | Article (article) |
| DOI: | 10.1109/LGRS.2010.2046618 |
| Digital: | 0 |
| Electronic Archiving: | grant_archive |
| Language: | en |
| Organization: | Max-Planck-Gesellschaft |
| School: | Biologische Kybernetik |
BibTeX
@article{6595,
title = {Spatio-Spectral Remote Sensing Image Classification With Graph Kernels},
journal = {IEEE Geoscience and Remote Sensing Letters},
abstract = {This letter presents a graph kernel for spatio-spectral remote sensing image classification with support vector machines (SVMs). The method considers higher order relations in the neighborhood (beyond pairwise spatial relations) to iteratively compute a kernel matrix for SVM learning. The proposed kernel is easy to compute and constitutes a powerful alternative to existing approaches. The capabilities of the method are illustrated in several multi- and hyperspectral remote sensing images acquired over both urban and agricultural areas.},
volume = {7},
number = {4},
pages = {741-745},
organization = {Max-Planck-Gesellschaft},
school = {Biologische Kybernetik},
month = oct,
year = {2010},
author = {Camps-Valls, G. and Shervashidze, N. and Borgwardt, K.},
doi = {10.1109/LGRS.2010.2046618},
month_numeric = {10}
}