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» Introduction to Pattern Recognition
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IBPRIA
2003
Springer
15 years 9 months ago
Incrementally Assessing Cluster Tendencies with a Maximum Variance Cluster Algorithm
A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the ...
Krzysztof Rzadca, Francesc J. Ferri
116
Voted
IBPRIA
2003
Springer
15 years 9 months ago
Bayesian Image Estimation from an Incomplete Set of Blurred, Undersampled Low Resolution Images
Abstract. This paper deals with the problem of reconstructing a highresolution image from an incomplete set of undersampled, blurred and noisy images shifted with subpixel displace...
Javier Mateos, Miguel Vega, Rafael Molina, Aggelos...
122
Voted
GBRPR
2009
Springer
15 years 8 months ago
From Random to Hierarchical Data through an Irregular Pyramidal Structure
This paper proposes to transform data scanned randomly in a well-defined space (e.g, Euclidean) along a hierarchical irregular pyramidal structure in an attempt reduce search time...
Rimon Elias, Mohab Al Ashraf, Omar Aly
IJCNN
2000
IEEE
15 years 8 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
ICML
2000
IEEE
15 years 8 months ago
Mutual Information in Learning Feature Transformations
We present feature transformations useful for exploratory data analysis or for pattern recognition. Transformations are learned from example data sets by maximizing the mutual inf...
Kari Torkkola, William M. Campbell