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RSFDGRC
2005
Springer
100views Data Mining» more  RSFDGRC 2005»
14 years 1 months ago
A Hybrid Approach to MR Imaging Segmentation Using Unsupervised Clustering and Approximate Reducts
Abstract. We introduce a hybrid approach to magnetic resonance image segmentation using unsupervised clustering and the rules derived from approximate decision reducts. We utilize ...
Sebastian Widz, Kenneth Revett, Dominik Slezak
TJS
2010
182views more  TJS 2010»
13 years 6 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
ICIP
2009
IEEE
13 years 5 months ago
A hierarchical graph-based markovian clustering approach for the unsupervised segmentation of textured color images
In this paper, a new unsupervised hierarchical approach to textured color images segmentation is proposed. To this end, we have designed a two-step procedure based on a grey-scale...
Rachid Hedjam, Max Mignotte
INTERSPEECH
2010
13 years 2 months ago
Unsupervised discovery and training of maximally dissimilar cluster models
One of the difficult problems of acoustic modeling for Automatic Speech Recognition (ASR) is how to adequately model the wide variety of acoustic conditions which may be present i...
Françoise Beaufays, Vincent Vanhoucke, Bria...
ISNN
2004
Springer
14 years 1 months ago
Unsupervised Learning for Hierarchical Clustering Using Statistical Information
This paper proposes a novel hierarchical clustering method that can classify given data without specified knowledge of the number of classes. In this method, at each node of a hie...
Masaru Okamoto, Nan Bu, Toshio Tsuji