Name
Title | ||
|---|---|---|
Spatial-Spectral Regularized Local Scaling Cut for Dimensionality Reduction in Hyperspectral Image Classification. |
Abstract | ||
|---|---|---|
Dimensionality reduction (DR) methods have attracted extensive attention to provide discriminative information and reduce the computational burden of hyperspectral image (HSI) classification. However, the DR methods face many challenges due to limited training samples with high-dimensional spectra. To address this issue, a graph-based spatial and spectral regularized local scaling cut (SSRLSC) for... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/LGRS.2018.2885809 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Training,Spectral analysis,Hyperspectral imaging,Manifolds,Dimensionality reduction,Linear programming | Computer vision,Data set,Dimensionality reduction,Pattern recognition,Matrix (mathematics),Projection (linear algebra),Hyperspectral imaging,Artificial intelligence,Pixel,Discriminative model,Scaling,Mathematics | Journal |
Volume | Issue | ISSN |
16 | 6 | 1545-598X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ramanarayan Mohanty | 1 | 2 | 2.39 |
| S. L. Happy | 2 | 51 | 9.11 |
| Aurobinda Routray | 3 | 337 | 52.80 |