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» A Novel Hybrid Neural Network for Data Clustering
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NN
2006
Springer
153views Neural Networks» more  NN 2006»
13 years 8 months ago
An incremental network for on-line unsupervised classification and topology learning
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Shen Furao, Osamu Hasegawa
CNSR
2005
IEEE
210views Communications» more  CNSR 2005»
13 years 10 months ago
A Framework for Self-Management of Hybrid Wireless Networks Using Autonomic Computing Principles
The dramatic increase in the number of mobile subscribers has put a significant resource and service provisioning strain on current cellular networks in particular in terms of mu...
Chong Shen, Dirk Pesch, James Irvine
VLSISP
2002
124views more  VLSISP 2002»
13 years 8 months ago
Agglomerative Learning Algorithms for General Fuzzy Min-Max Neural Network
In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...
Bogdan Gabrys
DICTA
2007
13 years 10 months ago
K-means Clustering for Classifying Unlabelled MRI Data
Texture analysis of the liver for the diagnosis of cirrhosis is usually region-of-interest (ROI) based. Integrity of the label of ROI data may be a problem due to sampling. This p...
Gobert N. Lee, Hiroshi Fujita
ESANN
2003
13 years 10 months ago
Semi-automatic acquisition and labelling of image data using SOMs
Abstract. Application of neural networks for real world object recognition suffers from the need to acquire large quantities of labelled image data. We propose a solution that acq...
Gunther Heidemann, Axel Saalbach, Helge Ritter