Segmentation of Stochastic Images using ... - Jacobs University

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List of Tables 3.1 The first ten one-dimensional Legendre-polynomials. The multi-dimensional polynomials up to degree nine are based on these polynomials and (3.40). . . . . . . . . . 32 3.2 Important distributions and the corresponding polynomials for the expansion. . . . . 32 3.3 The first ten one-dimensional Hermite-polynomials. The construction of the multidimensional polynomials up to degree 9 is based on these polynomials and (3.40). . . 33 6.1 Comparison of the execution times (in sec) of the discretization methods. . . . . . . 64 117
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Segmentation of Stochastic Images u
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Abstract The task of segmentation,
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7.5 Segmentation of Stochastic Imag
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Chapter 1 Introduction The developm
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Figure 1.3: This thesis combines fi
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the presentation of the stochastic
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Chapter 2 Image Segmentation and Li
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Chapter 3 SPDEs and Polynomial Chao
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Chapter 4 Discretization of SPDEs F
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Chapter 4 Discretization of SPDEs 4
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Chapter 4 Discretization of SPDEs a
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Chapter 5 Stochastic Images
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Chapter 5 Stochastic Images Figure
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Chapter 5 Stochastic Images like qu
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Chapter 5 Stochastic Images Figure
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Chapter 6 Segmentation of Stochasti
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6.1 Random Walker Segmentation on S
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Page 77 and 78: 6.2 Ambrosio-Tortorelli Segmentatio
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Page 121 and 122: List of Figures 1.1 Left: CT image
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Page 132 and 133: Bibliography [29] V. Caselles, F. C
Page 134 and 135: Bibliography [62] J. Gubner. Probab
Page 136 and 137: Bibliography [97] M. Matsumoto and
Page 138 and 139: Bibliography [129] T. Preusser and
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Segmentation of Stochastic Images using ... - Jacobs University

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