Name
Title | ||
|---|---|---|
Numeric and symbolic data fusion: a soft computing approach to remote sensing images analysis |
Abstract | ||
|---|---|---|
An expert system approach for image classification according to expert knowledge about best sites for vegetation classes is described. Uncertainty management is solved by a certainty factor approach. The numerical and symbolic data fusion is viewed as an updating process. The fusion approach is then described. A neural classifier applied to image data is the first source. A set of fuzzy neural networks representing expert knowledge constitutes the second source. A conjunctive combination based on evidence theory is applied. Finally, a possibility theory-based pooling aggregation rule is presented. These three approaches are applied to a vegetation classification problem. |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1016/S0167-8655(96)00093-1 | Pattern Recognition Letters |
Keywords | Field | DocType |
satellite image classification,evidence and possibility theory,neural networks,symbolic data fusion,information fusion,soft computing approach,images analysis,possibility theory,data fusion,neural network,soft computing,expert system,image classification,fuzzy neural network | Data mining,Pattern recognition,Computer science,Pooling,Expert system,Possibility theory,Sensor fusion,Artificial intelligence,Soft computing,Artificial neural network,Classifier (linguistics),Contextual image classification | Journal |
Volume | Issue | ISSN |
17 | 13 | Pattern Recognition Letters |
Citations | PageRank | References |
9 | 1.75 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jacky Desachy | 1 | 34 | 9.25 |
| Ludovic Roux | 2 | 51 | 7.25 |
| El-hadi Zahzah | 3 | 342 | 16.68 |