Name
Abstract | ||
|---|---|---|
This paper presents a self-organizing neural network approach, known as multiple self-organizing maps (MSOMs), to multisource data fusion and compound classification. The authors use the Kohonen SOM as a building block to set up a design framework for a range of classifiers. They demonstrate that the MSOM is suitable for multisource fusion, where the issues of high dimensionality, complex characte... |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1109/36.763298 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | Field | DocType |
Self organizing feature maps,Artificial neural networks,Brain modeling,Australia,Biological system modeling,Statistical distributions,Neural networks,Remote sensing,Solid modeling | Data processing,Remote sensing,Image processing,Self-organizing map,Artificial intelligence,Contextual image classification,Artificial neural network,Computer vision,Sensor fusion,Curse of dimensionality,Solid modeling,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
37 | 3 | 0196-2892 |
Citations | PageRank | References |
10 | 2.11 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weijian Wan | 1 | 11 | 2.48 |
| Donald Fraser | 2 | 78 | 8.29 |