Hierarchical Neural Networks Utilising Dempster-Shafer Evidence Theory

Author:

Fay Rebecca,Schwenker Friedhelm,Thiel Christian,Palm Günther

Publisher

Springer Berlin Heidelberg

Reference22 articles.

1. Chen, Y., Crawford, M., Ghosh, J.: Integrating support vector machines in a hierarchical output space decomposition framework. In: IEEE International Geoscience and Remote Sensing Symposium, vol. II, pp. 949–952 (2004)

2. Kumar, S., Ghosh, J., Crawford, M.: Hierarchical fusion of multiple classifiers for hyperspectral data analysis. International Journal on Pattern Analysis and Applications 5(2), 210–220 (2002)

3. Cheong, S., Oh, S., Lee, S.Y.: Support vector machines with binary tree architecture for multi-class classification. Neural Information Processing - Letters and Reviews 2(3), 47–51 (2004)

4. Schwenker, F.: Solving multi-class pattern recognition problems with tree structured support vector machines. In: Radig, B., Florczyk, S. (eds.) Mustererkennung 2001, pp. 283–290. Springer, Heidelberg (2001)

5. Simon, S., Schwenker, F., Kestler, H.A., Kraetzschmar, G.K., Palm, G.: Hierarchical object classification for autonomous mobile robots. In: International Conference on Artificial Neural Networks (ICANN), pp. 831–836 (2002)

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