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» Neural Network Classification and Prior Class Probabilities
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2006
14 years 11 months ago
Supervised neuronal approaches for EEG signal classification: Experimental studies
Using artificial neural networks for Electroencephalogram (EEG) signal interpretation is a very challenging tasks for several reasons. The first class of reasons refers to the nat...
Frédéric Alexandre, Kerkeni Nizar, K...
ISD
1999
Springer
213views Database» more  ISD 1999»
15 years 1 months ago
A Probabilistic Approach to Environmental Change Detection with Area-Class Map Data
One of the primary methods of studying change in the natural and man-made environment is that of comparison of multi-date maps and images of the earth's surface. Such comparis...
Christopher B. Jones, J. Mark Ware, David R. Mille...
74
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IJPRAI
2000
101views more  IJPRAI 2000»
14 years 9 months ago
An Integer Recurrent Artificial Neural Network for Classifying Feature Vectors
: The main contribution of this report is the development of an integer recurrent artificial neural network (IRANN) for classification of feature vectors. The network consists both...
Roelof K. Brouwer
IJCNN
2007
IEEE
15 years 3 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
APIN
2004
116views more  APIN 2004»
14 years 9 months ago
Neural Learning from Unbalanced Data
This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We conducted the study on three differen...
Yi Lu Murphey, Hong Guo, Lee A. Feldkamp