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Titlebook: Advances in Pattern Recognition; Joint IAPR Internati Francesc J. Ferri,José M. Iñesta,Pavel Pudil Conference proceedings 2000 Springer-Ver

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Conference proceedings 2000The book offers topical sections on hybrid and combined methods, document image analysis, grammar and language methods, structural matching, graph-based methods, shape analysis, clustering and density estimation, object recognition, general methodology, and feature extraction and selection.
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https://doi.org/10.1007/978-94-024-1020-4, starting weights, a noise injection to original training vectors, to targets, and to the weights) on a result. Some of the discussed methods to control complexity are almost not discussed in the literature yet.
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https://doi.org/10.1007/978-1-4020-9143-8t is more likely to provide the correct classification. Reported results on the classification of different data sets show that dynamic classifier selection based on MCS behaviour is an effective operation mechanism for MCSs.
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G. Ambika,K.P. Harikrishnan,R. Misracan then be used for various classification and clustering problems. Here, the method is applied to an image database retrieval problem and an object image classification problem, and is shown to give promising results.
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Markus Klein,Martin Freitag,Johannes Janickatrospective conversion consists in identifying each entity of the document and its structures as well. The structural classification method based on graph comparison is used at several levels of this process. Graph comparison is also used in the learning of generic entities.
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Complex Effects in Large Eddy Simulationsso that the representation of a class of assemblies becomes especially compact. This general representation scheme allows to automatically derive hierarchical structural descriptions of individual assemblies by means of computer vision.
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Complex Dynamics and Morphogenesis combine the complementary measurement information that might be available to different experts. This process is embodied in an overall architecture which shows why the fusion of raw expert outputs is a nonlinear function of the expert outputs and how this function can be realised as a sequence of relatively simple processes.
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