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ESANN
2003
15 years 8 months ago
Approximation of Function by Adaptively Growing Radial Basis Function Neural Networks
In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learn...
Jianyu Li, Siwei Luo, Yingjian Qi
IJON
2002
123views more  IJON 2002»
15 years 6 months ago
N-bit parity neural networks: new solutions based on linear programming
In this paper, the N-bit parity problem is solved with a neural network that allows direct connections between the input layer and the output layer. The activation function used i...
Derong Liu, Myron E. Hohil, Stanley H. Smith
ICCV
1999
IEEE
16 years 8 months ago
Neurocalibration: A Neural Network That Can Tell Camera Calibration Parameters
Camera calibration is a primary crucial step in many computer vision tasks. In this paper we present a new neural approach for camera calibration. Unlike some existing neural appr...
Moumen T. Ahmed, Elsayed E. Hemayed, Aly A. Farag
IJCNN
2006
IEEE
16 years 20 days ago
C2FS: An Algorithm for Feature Selection in Cascade Neural Networks
Wrapper-based feature selection is attractive because wrapper methods are able to optimize the features they select to the specific learning algorithm. Unfortunately, wrapper met...
Lars Backstrom, Rich Caruana
ECAL
1995
Springer
15 years 10 months ago
Evolving Artificial Neural Networks that Develop in Time
Although recently there has been an increasing interest in studing genetically-based development using Artificial Life models, the mapping of the genetic information into the phen...
Stefano Nolfi, Domenico Parisi