Name
Abstract | ||
|---|---|---|
In this paper, a new regularization method for both parametric and nonparametric feature extraction algorithms is proposed for mitigating the singularity of within-class scatter matrix and improving hyperspectral data feature extraction. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/IGARSS.2003.1294244 | IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES |
Keywords | DocType | Citations |
regularization, feature extraction, hyperspectral data classification | Conference | 10 |
PageRank | References | Authors |
1.15 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bor-Chen Kuo | 1 | 131 | 13.11 |
| liwei ko | 2 | 10 | 1.15 |
| chiahao pai | 3 | 10 | 1.15 |
| David A. Landgrebe | 4 | 807 | 125.38 |