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Pattern Recognition with Fuzzy Objective Function Algorithms
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Citations
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Cluster Analysis of Biomedical Image Time-Series
Axel Wismüller,Oliver F. Lange,Dominik R. Dersch,Gerda Leinsinger,Klaus Hahn,Benno Pütz,Dorothee P. Auer +6 more
TL;DR: Applications to functional MRI data analysis for human brain mapping, dynamic contrast-enhanced perfusion MRI for the diagnosis of cerebrovascular disease, and magnetic resonance mammography for the analysis of suspicious lesions in patients with breast cancer are presented.
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A Novel Validity Index for Determination of the Optimal Number of Clusters
TL;DR: The structural characteristics of clusters are investigated in the partitioning process and two partition functions, which show opposite properties around the optimal cluster number, are found and a new cluster validity index is presented.
Journal ArticleDOI
Extracting web user profiles using relational competitive fuzzy clustering
TL;DR: The notion of a "user session" is defined as being a temporally compact sequence of Web accesses by a user and a new distance measure between two Web sessions that captures the organization of a Web site is defined.
Journal ArticleDOI
General Type-2 Fuzzy C-Means Algorithm for Uncertain Fuzzy Clustering
Ondrej Linda,Milos Manic +1 more
TL;DR: The GT2 FCM algorithm was found to balance the performance of T1 FCM algorithms in various uncertain pattern recognition tasks and to provide increased robustness in situations where noisy or insufficient training data are present.
Journal ArticleDOI
Segmentation of color lip images by spatial fuzzy clustering
TL;DR: The proposed spatial fuzzy clustering algorithm is able to take into account both the distributions of data in feature space and the spatial interactions between neighboring pixels during clustering.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Book
Introduction to Statistical Pattern Recognition
TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters
TL;DR: In this paper, two fuzzy versions of the k-means optimal, least squared error partitioning problem are formulated for finite subsets X of a general inner product space, and the extremizing solutions are shown to be fixed points of a certain operator T on the class of fuzzy, k-partitions of X, and simple iteration of T provides an algorithm which has the descent property relative to the LSE criterion function.