Titlebook: Bayesian Inference in Wavelet-Based Models; Peter Müller,Brani Vidakovic Book 1999 Springer Science+Business Media New York 1999 Markov mo

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Human Ear Recognition by Computerity estimation. The common theme in all three applications is the lack of posterior independence for the wavelet coefficients ... In contrast, most commonly considered applications of wavelet decompositions in Statistics are based on a setup which implies . independent coefficients, essentially redu

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Human Ear Recognition by Computerlocal procedure, since wavelet coefficients characterize the local regularity of a function. Although a wavelet transform has decorrelating properties, structures in images, like edges, are never decor-related completely, and these structures appear in the wavelet coefficients. We therefore introduc

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Ear Detection and Recognition in 2D and 3D,ctable multiresolution paradigm. In addition to providing a very natural and useful framework for modeling and processing images, Bayesian multiscale analysis is often much less computationally demanding compared to classical Markov random field models. This chapter focuses on a probabilistic graph

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Lecture Notes in Statisticshttp://image.papertrans.cn/b/image/181852.jpg

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