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PRL
2006
124views more  PRL 2006»
14 years 11 months ago
Parameter selection for suppressed fuzzy c-means with an application to MRI segmentation
This paper presents an algorithm, called the modified suppressed fuzzy c-means (MS-FCM), that simultaneously performs clustering and parameter selection for the suppressed fuzzy c...
Wen-Liang Hung, Miin-Shen Yang, De-Hua Chen
BMCBI
2008
142views more  BMCBI 2008»
14 years 12 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
KI
2010
Springer
14 years 10 months ago
An Extensible Modular Recognition Concept That Makes Activity Recognition Practical
Abstract. In mobile and ubiquitous computing, there is a strong need for supporting different users with different interests, needs, and demands. Activity recognition systems for c...
Martin Berchtold, Matthias Budde, Hedda Rahel Schm...
162
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Book
640views
16 years 10 months ago
Introduction to Pattern Recognition
"Pattern recognition techniques are concerned with the theory and algorithms of putting abstract objects, e.g., measurements made on physical objects, into categories. Typical...
Sargur Srihari
CVPR
1996
IEEE
15 years 3 months ago
Pattern Rejection
The e ciency of pattern recognition is particularly crucial in two scenarios; whenever there are a large number of classes to discriminate, and, whenever recognition must be perfo...
Simon Baker, Shree K. Nayar