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检索条件"主题词=kernel-based pattern recognition"

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The neutral point method for kernel-based combination of disjoint training data in multi-modal pattern recognition

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7th International Workshop on Multiple Classifier Systems

作者： Windridge, David Mottl, Vadim Tatarchuk, Alexander Eliseyev, Andrey Univ Surrey Ctr Vis Speech & Signal Proc Guildford GU2 7XH Surrey England Russian Acad Sci Ctr Comp Moscow 119991 Russia Moscow Phys Tech Inst Inst Per 9 Dolgoprudnyi 141700 Russia

ISBN: (纸本)9783540724810

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 to approach the matter from a kernel-based perspective. By interpreting the aggregate of disjoint training sets as an entire data set with missing inter-modality measurements to be filled in by appropriately chosen substitutes, we arrive at a novel kemel-based technique, the neutral-point method. On further theoretical analysis, it transpires that the method is, in structural terms, a kernel-based analog of the well-known sum rule combination scheme. We therefore expect the method to exhibit similar error-canceling behavior, and thus constitute a robust and conservative strategy for the treatment of kemel-based multi-modal data.

关键词： kernel-based pattern recognition combining modalities kernel fusion classifier fusion

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The relationship between kernel and classifier fusion in kernel-based multi-modal pattern recognition: An experimental study

The relationship between kernel and classifier fusion in ker...

引用

6th International Conference on Machine Learning and Cybernetics

作者： Windridge, David Mottl, Vadim Tatarchuk, Alexander Eliseyev, Andrey Univ Surrey Ctr Vis Speech & Signal Proc Stag Hill Guildford GU2 7XH Surrey England Russian Acad Sci Comp Ctr Moscow 119991 Russia Moscow Inst Phys & Tech Moscow 141700 Russia

ISBN: (纸本)9781424409723

Two distinct principles of multi-modal kernel-based pattern recognition, kernel and classifier fusion, are demonstrated to share common underlying characteristics via the use of a novel kernel-based technique for combining modalities under fully general conditions, namely, the neutral-point method. This method presents a conservative kernel-based strategy for dealing with missing and disjoint training data in independent measurement modalities that can be theoretically shown to default to the Sum Rule classification scheme. Results of comparative experiments indicate that the neutral-point technique loses relatively little classification information with respect to coincident training data, and is in fact preferable for independent kernels produced by different physical modalities due to its better error-cancellation properties.

关键词： kernel-based pattern recognition combining modalities kernel fusion classifier fusion

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Combining pattern recognition modalities at the sensor level via kernel fusion

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7th International Workshop on Multiple Classifier Systems

作者： Mottl, Vadim Tatarchuk, Alexander Sulimova, Valentina Krasotkina, Olga Seredin, Oleg Russian Acad Sci Ctr Comp Moscow 117968 Russia Tula State Univ Tula Russia

ISBN: (纸本)9783540724810

The problem of multi-modal pattern recognition is considered under the assumption that the kemel-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 modalities, actually, at the sensor level. From this point of view, the known kernel fusion techniques, including Relevance and Support kernel Machines, offer a toolkit of combining pattern recognition modalities. We propose an SVM-based quasi-statistical approach to multi-modal pattern recognition which covers both of these modes of kernel fusion.

关键词： kernel-based pattern recognition support vector machines combining modalities kernel fusion

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