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Nonlinear transformation of one image plane relative to another by spatially constrained elastic matching of two pixel grids is proposed as a technique of measuring image similarity for the purpose of featureless face identi cation. The elastic matching algorithm is devised as a combination of two dynamic programming procedures applied independently to each(More)
Multiple modalities present potential difficulties for kernel-based pattern recognition in consequence of the lack of inter-modal kernel measures. This is particularly apparent when training sets for the differing modalities are disjoint. Thus, while it is always possible to consider the problem at the classifier fusion level, it is conceptually preferable(More)
The problem of multi-modal pattern recognition is considered under the assumption that the kernel-based approach is applicable within each particular modality. The Cartesian product of the linear spaces into which the respective kernels embed the output scales of single sensor is employed as an appropriate joint scale corresponding to the idea of combining(More)
The featureless methodology is applied to the class of pattern recognition problems in which the adopted pairwise similarity measure possesses the most fundamental property of inner product to form a nonnegative de nite matrix for any nite assembly of objects. It is proposed to treat the set of all feasible objects of recognition as a subset of isolated(More)
A massive data set is considered as a set of experimentally acquired values of a number of variables each of which is associated with the respective node of an undirected adjacency graph that presets the xed structure of the data set. The class of data analysis problems under consideration is outlined by the assumption that the ultimate aim of processing(More)
The featureless pattern recognition methodology based on measuring some numerical characteristics of similarity between pairs of entities is applied to the problem of protein fold classification. In computational biology, a commonly adopted way of measuring the likelihood that two proteins have the same evolutionary origin is calculating the so-called(More)
In multimodal biometric information fusion, it is common to encounter missing modalities in which matching cannot be performed. As a result, at the match score level, this implies that scores will be missing. We address the multimodal fusion problem involving missing modalities (scores) using support vector machines (SVMs) with the neutral point(More)
As an adjunct to the classical pattern recognition theory dealing with single objects, a new approach to supervised pattern recognition is proposed for a variety of practical problems in which the class-memberships of several interrelated objects making an entire data array are to be estimated jointly. It is assumed, first, that the known structure of the(More)
The problem of signature verification is considered within the bounds of the kernel-based methodology of pattern recognition, more specifically, SVM principle of machine learning. A kernel in the set of signatures can be defined in different ways and it is impossible to choose the most appropriate kernel a priori. We propose a principle of fusing several(More)
The problem of prospecting oil and gas reserves in the crystalline basement of the Earth mantle by way of a combined interpretation of seismic data registered on the daylight surface and direct information from a sparse net of exploratory wells is considered as pattern recognition problem in which the role of objects whose class membership is to be(More)