Name
Abstract | ||
|---|---|---|
In this paper we present a new type of Radial Basis Function (RBF) Neural Network based in order statistics for image classification applications. The proposed neural network uses the Median M-type (MM) estimator in the scheme of radial basis function to train the neural network. The proposed network is less biased by the presence of outliers in the training set and was proved an accurate estimation of the implied probabilities. From simulation results we show that the proposed neural network has better classification capabilities in comparison with other RBF based algorithms. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-76631-5_15 | MICAI |
Keywords | Field | DocType |
median m-type,image classification application,proposed network,order statistic,implied probability,radial basis function neural,new type,radial basis function,neural network,better classification capability,accurate estimation,proposed neural network | Feedforward neural network,Radial basis function network,Radial basis function,Pattern recognition,Computer science,Stochastic neural network,Probabilistic neural network,Time delay neural network,Artificial intelligence,Artificial neural network,Machine learning,Estimator | Conference |
Volume | ISSN | ISBN |
4827 | 0302-9743 | 3-540-76630-8 |
Citations | PageRank | References |
1 | 0.36 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José A. Moreno-Escobar | 1 | 2 | 0.73 |
| Francisco J. Gallegos-Funes | 2 | 66 | 10.19 |
| Volodymyr Ponomaryov | 3 | 38 | 10.37 |
| Jose M. De-La-Rosa-Vazquez | 4 | 1 | 0.36 |