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ESANN
2003
13 years 10 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
CVPR
2007
IEEE
14 years 10 months ago
Joint Priors for Variational Shape and Appearance Modeling
We are interested in modeling the variability of different images of the same scene, or class of objects, obtained by changing the imaging conditions, for instance the viewpoint o...
Jeremy D. Jackson, Anthony J. Yezzi, Stefano Soatt...
IJCNN
2008
IEEE
14 years 3 months ago
Kernel methods for fMRI pattern prediction
Abstract— In this paper, we present an effective computational approach for learning patterns of brain activity from the fMRI data. The procedure involved correcting motion artif...
Yizhao Ni, Carlton Chu, Craig J. Saunders, John As...
ICIP
2010
IEEE
13 years 6 months ago
Saliency detection based on short-term sparse representation
Representation and measurement are two important issues for saliency models. Different with previous works that learnt sparse features from large scale natural statistics, we prop...
Xiaoshuai Sun, Hongxun Yao, Rongrong Ji, Pengfei X...
CONNECTION
2006
172views more  CONNECTION 2006»
13 years 8 months ago
Temporal sequence detection with spiking neurons: towards recognizing robot language instructions
We present an approach for recognition and clustering of spatio temporal patterns based on networks of spiking neurons with active dendrites and dynamic synapses. We introduce a n...
Christo Panchev, Stefan Wermter