Guy gilboa (7 Ergebnisse)
Sprache: Englisch
Verlag: Springer 2019
Serie: Advances in Computer Vision and Pattern Recognition, Buch 66 von 86. Buch 66 von 86 - Advances in Computer Vision and Pattern Recognition
- Softcover
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Sprache: Englisch
Verlag: Springer 2018
Serie: Advances in Computer Vision and Pattern Recognition, Buch 66 von 86. Buch 66 von 86 - Advances in Computer Vision and Pattern Recognition
- Hardcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
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Zustand: New. In.
Sprache: Englisch
Verlag: Springer 2019
Serie: Advances in Computer Vision and Pattern Recognition, Buch 66 von 86. Buch 66 von 86 - Advances in Computer Vision and Pattern Recognition
- Softcover
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Taschenbuch. Zustand: Neu. Nonlinear Eigenproblems in Image Processing and Computer Vision | Guy Gilboa | Taschenbuch | Advances in Computer Vision and Pattern Recognition | xx | Englisch | 2019 | Springer | EAN 9783030093396 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[…dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer 2018
Serie: Advances in Computer Vision and Pattern Recognition, Buch 66 von 86. Buch 66 von 86 - Advances in Computer Vision and Pattern Recognition
- Hardcover
Anbieter: Revaluation Books, Exeter, , Vereinigtes KönigreichRevaluation Books
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Hardcover. Zustand: Brand New. 194 pages. 9.25x6.10x0.67 inches. In Stock.
Sprache: Englisch
Verlag: Springer International Publishing, Springer International Publishing 2019
Serie: Advances in Computer Vision and Pattern Recognition, Buch 66 von 86. Buch 66 von 86 - Advances in Computer Vision and Pattern Recognition
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This unique text/reference presents a fresh look at nonlinear processing through nonlinear eigenvalue analysis, highlighting how one-homogeneous convex functionals can induce nonlinear operators that can be analyzed within an eigenvalue framework. Th…e text opens with an introduction to the mathematical background, together with a summary of classical variational algorithms for vision. This is followed by a focus on the foundations and applications of the new multi-scale representation based on non-linear eigenproblems. The book then concludes with a discussion of new numerical techniques for finding nonlinear eigenfunctions, and promising research directions beyond the convex case.Topics and features: introduces the classical Fourier transform and its associated operator and energy, and asks how these concepts can be generalized in the nonlinear case; reviews the basic mathematical notion, briefly outlining the use of variational and flow-based methods to solve image-processingand computer vision algorithms; describes the properties of the total variation (TV) functional, and how the concept of nonlinear eigenfunctions relate to convex functionals; provides a spectral framework for one-homogeneous functionals, and applies this framework for denoising, texture processing and image fusion; proposes novel ways to solve the nonlinear eigenvalue problem using special flows that converge to eigenfunctions; examines graph-based and nonlocal methods, for which a TV eigenvalue analysis gives rise to strong segmentation, clustering and classification algorithms; presents an approach to generalizing the nonlinear spectral concept beyond the convex case, based on pixel decay analysis; discusses relations to other branches of image processing, such as wavelets and dictionary based methods.This original work offers fascinating new insights into established signal processing techniques, integrating deep mathematical concepts from a range of different fields, which will be of great interest to all researchers involved with image processing and computer vision applications, as well as computations for more general scientific problems.
Sprache: Englisch
Verlag: Springer International Publishing 2018
Serie: Advances in Computer Vision and Pattern Recognition, Buch 66 von 86. Buch 66 von 86 - Advances in Computer Vision and Pattern Recognition
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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EUR 128,39
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This unique text/reference presents a fresh look at nonlinear processing through nonlinear eigenvalue analysis, highlighting how one-homogeneous convex functionals can induce nonlinear operators that can be analyzed within an eigenvalue framework. The text…opens with an introduction to the mathematical background, together with a summary of classical variational algorithms for vision. This is followed by a focus on the foundations and applications of the new multi-scale representation based on non-linear eigenproblems. The book then concludes with a discussion of new numerical techniques for finding nonlinear eigenfunctions, and promising research directions beyond the convex case.Topics and features: introduces the classical Fourier transform and its associated operator and energy, and asks how these concepts can be generalized in the nonlinear case; reviews the basic mathematical notion, briefly outlining the use of variational and flow-based methods to solve image-processingand computer vision algorithms; describes the properties of the total variation (TV) functional, and how the concept of nonlinear eigenfunctions relate to convex functionals; provides a spectral framework for one-homogeneous functionals, and applies this framework for denoising, texture processing and image fusion; proposes novel ways to solve the nonlinear eigenvalue problem using special flows that converge to eigenfunctions; examines graph-based and nonlocal methods, for which a TV eigenvalue analysis gives rise to strong segmentation, clustering and classification algorithms; presents an approach to generalizing the nonlinear spectral concept beyond the convex case, based on pixel decay analysis; discusses relations to other branches of image processing, such as wavelets and dictionary based methods.This original work offers fascinating new insights into established signal processing techniques, integrating deep mathematical concepts from a range of different fields, which will be of great interest to all researchers involved with image processing and computer vision applications, as well as computations for more general scientific problems.
Sprache: Englisch
Verlag: Springer 2018
Serie: Advances in Computer Vision and Pattern Recognition, Buch 66 von 86. Buch 66 von 86 - Advances in Computer Vision and Pattern Recognition
- Hardcover
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