Name
Abstract | ||
|---|---|---|
In this paper we present the capability of the Median M-Type Radial Basis Function (MMRBF) Neural Network in 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. Other RBF based algorithms were compared with our approach. From simulation results we observe that the MMRBF neural network has better classification capabilities. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-76725-1_55 | CIARP |
Keywords | Field | DocType |
median m-type radial basis,image classification application,median m-type,mmrbf neural network,neural network,simulation result,radial basis function,better classification capability,function neural network,proposed neural network,image classification | Feedforward neural network,Radial basis function network,Radial basis function,Pattern recognition,Activation function,Computer science,Probabilistic neural network,Time delay neural network,Artificial intelligence,Artificial neural network,Contextual image classification | Conference |
Volume | ISSN | ISBN |
4756 | 0302-9743 | 3-540-76724-X |
Citations | PageRank | References |
1 | 0.36 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José A. Moreno-Escobar | 1 | 2 | 0.73 |
| Francisco J. Gallegos-Funes | 2 | 66 | 10.19 |
| Volodymyr I. Ponomaryov | 3 | 124 | 18.38 |