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Pattern Recognition with Fuzzy Objective Function Algorithms
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Citations
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Numerical Classification of Proximity Data with Assignment Measures
TL;DR: In this article, an approach to numerical classification is described, which treats the assignment of objects to types as a continuous variable, called an assignment measure, which allows one not only to determine the types of objects, but also to see relationships among the objects of the same type and among the types themselves.
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Thermal error modelling of machine tools based on ANFIS with fuzzy c-means clustering using a thermal imaging camera
TL;DR: In this article, an adaptive Neuro-Fuzzy Inference System with fuzzy c-means clustering (FCM-ANFIS) was employed to design the thermal prediction model.
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Unsupervised segmentation of polarimetric SAR data using the covariance matrix
TL;DR: A method for unsupervised segmentation of polarimetric synthetic aperture radar (SAR) data into classes of homogeneous microwave polarIMetric backscatter characteristics is presented.
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A new clustering technique for function approximation
TL;DR: A new clustering technique, specially designed for function approximation problems, is presented, which improves the performance of the approximator system obtained, compared with other models derived from traditional classification oriented clustering algorithms and input-output clustering techniques.
Journal ArticleDOI
Kernel-induced fuzzy clustering of image pixels with an improved differential evolution algorithm
Swagatam Das,Sudeshna Sil +1 more
TL;DR: A modified differential evolution (DE) algorithm is presented for clustering the pixels of an image in the gray-scale intensity space and has an edge over a few state-of-the-art algorithms for automatic multi-class image segmentation.
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.