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» On the use of spiking neural network for EEG classification
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IDEAL
2005
Springer
14 years 2 months ago
Evolving Neural Networks for the Classification of Malignancy Associated Changes
Malignancy Associated Changes are subtle changes to the nuclear texture of visually normal cells in the vicinity of a cancerous or precancerous lesion. We describe a classifier for...
Jennifer Hallinan
ICPR
2002
IEEE
14 years 1 months ago
Contour Features for Colposcopic Image Classification by Artificial Neural Networks
This article presents colposcopic image classification based on contour parameters used in a comparison study of different artificial neural networks and the knearest neighbors re...
Isabelle Claude, Renaud Winzenrieth, Philippe Poul...
IJCNN
2000
IEEE
14 years 1 months ago
A 2D Neuromorphic VLSI Architecture for Modeling Selective Attention
Selectiveattentionis a mechanismsused to sequentiallyselectthe spatiallocationsof salientregionsin the sensor’sfieldof view. This mechanism overcomesthe problem of flooding limi...
Giacomo Indiveri
IEEEICCI
2003
IEEE
14 years 1 months ago
Signal Classification through Multifractal Analysis and Complex Domain Neural Networks
This paper describes a system capable of classifying stochastic, self-affine, nonstationary signals produced by nonlinear systems. The classification and analysis of these signals...
Witold Kinsner, V. Cheung, K. Cannons, J. Pear, T....
IJCNN
2000
IEEE
14 years 1 months ago
Incorporating a priori Knowledge into Initialized Weights for Neural Classifier
Artificial neural networks (ANN), esp. multilayer perceptrons (MLP) have been widely used in pattern recognition and classification. Nevertheless, how to incorporate a priori know...
Zhe Chen, Tian-Jin Feng, Zweitze Houkes