…matrix . is the dissimilarity between the sensor inputs for objects and . is a feature defined by pairwise dissimilarities to . is a dissimilarity-based representation for . , defines…

…The dissimilarity representation has a strong resemblance to a kernel. There are, however, essential differences in assumptions and usage. Here they will be summarized and illustrated by some…

dissimilarity space in which statistical recognition procedures can be used. Distances and densities are now clearly given their own domains: representation and generalization. When applied to structural object descriptions, it…

…machine learning can be used for this representation to build good classifiers. Also in case a dissimilarity measure is just approximately euclidean this can be a useful procedure. Like in…

Random Representations

…The goal of representation is in pattern recognition to map objects into a domain in which they can be compared. Usually, this domain is a vector space. It…

Representation and generalization

…all the objects in a domain that is open for computations on object differences. This domain is called a representation. Define a good representation The process of finding a good…

combining the four sets. In some papers and presentations on the dissimilarity representation the flow-cytometer application was used as an illustration of possibilities. After some years we published an overview…

What is the core business of pattern recognition?

…and Recognition in Vision, MIT Press, Cambridge, 1999. [3]. E. Pekalska and R.P.W. Duin, The Dissimilarity Representation for Pattern Recognition, Foundations and Applications, World Scientific, Singapore, 2005, 1-607.  …

PRTools: building blocks for pattern recognition

…for raw, unprocessed data. CLASSIFICATION_PROCEDURE is a mapping combining representation and generalization. We will use Fisher’s Linear Discriminant for the latter: CLASSIFICATION_PROCEDURE = REPRESENTATION * fisherc This combines two mappings….

Plato and Aristotle

…Towards the unification of structural and statistical pattern recognition, Pattern Recognition Letters, vol. 33, no. 7, pp. 811-825, 2012. [5] E. Pekalska and R.P.W. Duin, The Dissimilarity Representation for Pattern…

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