Name
Abstract | ||
|---|---|---|
The classification of multisensor data sets, consisting of multitemporal synthetic aperture radar data and optical imagery, is addressed. The concept is based on the decision fusion of different outputs. Each data source is treated separately and classified by a support vector machine (SVM). Instead of fusing the final classification outputs (i.e., land cover classes), the original outputs of each... |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TGRS.2007.898446 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | Field | DocType |
Support vector machines,Support vector machine classification,Classification tree analysis,Remote monitoring,Remote sensing,Artificial neural networks,Adaptive optics,Laser radar,Optical sensors,Decision trees | Structured support vector machine,Decision tree,Data set,Pattern recognition,Synthetic aperture radar,Support vector machine,Remote sensing,Sensor fusion,Artificial intelligence,Classifier (linguistics),Artificial neural network,Mathematics | Journal |
Volume | Issue | ISSN |
45 | 12 | 0196-2892 |
Citations | PageRank | References |
133 | 6.15 | 22 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Björn Waske | 1 | 435 | 24.75 |
| JÓn Atli Benediktsson | 2 | 635 | 28.85 |