Sciweavers

IJON
2008
133views more  IJON 2008»
13 years 11 months ago
A multi-objective approach to RBF network learning
The problem of inductive supervised learning is discussed in this paper within the context of multi-objective (MOBJ) optimization. The smoothness-based apparent (effective) comple...
Illya Kokshenev, Antônio de Pádua Bra...
MVA
2000
172views Computer Vision» more  MVA 2000»
14 years 1 months ago
Partial Face Extraction and Recognition Using Radial Basis Function Networks
work, applies a nonlinear transformation from the input space to the hidden space. The output layer Partial face images, e.g.1 eyes, nose, and ear supplies the response of the netw...
Nan He, Kiminori Sato, Yukitoshi Takahashi
SNPD
2003
14 years 1 months ago
RBF Networks from Boosted Rules
A novel method for constructing RBF networks is presented. It is based on Boosting, an ensemble method that combines several classifiers obtained using any other classification ...
Juan José Rodríguez, Vanesa Paniego,...
CBMS
1997
IEEE
14 years 4 months ago
Radial basis function-based image segmentation using a receptive field
This paper presents a novel method for CT head image automatic segmentation. The images are obtained from patients having the spontaneous intra cerebral brain hemorrhage ICH. Th...
Domagoj Kovacevic, Sven Loncaric
IJCNN
2008
IEEE
14 years 7 months ago
Fully complex-valued radial basis function networks for orthogonal least squares regression
— We consider a fully complex-valued radial basis function (RBF) network for regression application. The locally regularised orthogonal least squares (LROLS) algorithm with the D...
Sheng Chen, Xia Hong, Chris J. Harris