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Condizione: As New. Unread book in perfect condition.

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Hardback. Condizione: As new. xix + 428 pp. book.

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Taschenbuch. Condizione: Neu. Neuware - In this Element, the authors consider fully discretized p-Laplacian problems (evolution, boundary value and variational problems) on graphs. The motivation of nonlocal continuum limits comes from the quest of understanding collective dynamics in large ensembles of interacting particles, which is a fundamental problem in nonlinear science, with applications ranging from biology to physics, chemistry and computer science. Using the theory of graphons, the authors give a unified treatment of all the above problems and establish the continuum limit for each of them together with non-asymptotic convergence rates. They also describe an algorithmic framework based proximal splitting to solve these discrete problems on graphs.…

hardcover. Condizione: Fair. Light cover wear, first blank page removed, otherwise good condition, text is unmarked.

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Condizione: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

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Paperback. Condizione: Brand New. 596 pages. 9.25x6.10x1.35 inches. In Stock.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings of the 8th International Conference onScale Space and Variational Methods in Computer Vision, SSVM 2021, which took place during May 16-20, 2021. The conference was planned to take place in Cabourg, France, but changed to an online format due to the COVID-19 pandemic.The 45 papers included in this volume were carefully reviewed and selected from a total of 64 submissions. They were organized in topical sections named as follows: scale space and partial differential equations methods; flow, motion and registration; optimization theory and methods in imaging; machine learning in imaging; segmentation and labelling; restoration, reconstruction and interpolation; and inverse problems in imaging.…

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Taschenbuch. Condizione: Neu. Scale Space and Variational Methods in Computer Vision | 8th International Conference, SSVM 2021, Virtual Event, May 16-20, 2021, Proceedings | Abderrahim Elmoataz (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xiv | Englisch | 2021 | Springer | EAN 9783030755485 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Hardback. Condizione: New. This thoroughly updated new edition presents state-of-the-art sparse and multiscale image and signal processing. It covers linear multiscale geometric transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Along with an up-to-the-minute description of required computation, it covers the latest results in inverse problem solving and regularization, sparse signal decomposition, blind source separation, in-painting, and compressed sensing. New chapters and sections cover multiscale geometric transforms for three-dimensional data (data cubes), data on the sphere (geo-located data), dictionary learning, and nonnegative matrix factorization. The authors wed theory and practice in examining applications in areas such as astronomy, including recent results from the European Space Agency's Herschel mission, biology, fusion physics, cold dark matter simulation, medical MRI, digital media, and forensics. MATLAB® and IDL code, available online at www.SparseSignalRecipes.info, accompany these methods and all applications.…

Condizione: New. pp.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This thoroughly updated new edition presents state-of-the-art sparse and multiscale image and signal processing. It covers linear multiscale geometric transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Along with an up-to-the-minute description of required computation, it covers the latest results in inverse problem solving and regularization, sparse signal decomposition, blind source separation, in-painting, and compressed sensing. New chapters and sections cover multiscale geometric transforms for three-dimensional data (data cubes), data on the sphere (geo-located data), dictionary learning, and nonnegative matrix factorization. The authors wed theory and practice in examining applications in areas such as astronomy, including recent results from the European Space Agency's Herschel mission, biology, fusion physics, cold dark matter simulation, medical MRI, digital media, and forensics. MATLAB® and IDL code, available online at SparseSignalRecipes.info, accompany these methods and all applications.…

Hardback. Condizione: New. This thoroughly updated new edition presents state-of-the-art sparse and multiscale image and signal processing. It covers linear multiscale geometric transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Along with an up-to-the-minute description of required computation, it covers the latest results in inverse problem solving and regularization, sparse signal decomposition, blind source separation, in-painting, and compressed sensing. New chapters and sections cover multiscale geometric transforms for three-dimensional data (data cubes), data on the sphere (geo-located data), dictionary learning, and nonnegative matrix factorization. The authors wed theory and practice in examining applications in areas such as astronomy, including recent results from the European Space Agency's Herschel mission, biology, fusion physics, cold dark matter simulation, medical MRI, digital media, and forensics. MATLAB® and IDL code, available online at www.SparseSignalRecipes.info, accompany these methods and all applications.…

Condizione: new. Questo è un articolo print on demand.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the proceedings of the 8th International Conference onScale Space and Variational Methods in Computer Vision, SSVM 2021, which took place during May 16-20, 2021. The conference was planned to take place in Cabourg, France, but changed to an online format due to the COVID-19 pandemic.The 45 papers included in this volume were carefully reviewed and selected from a total of 64 submissions. They were organized in topical sections named as follows: scale space and partial differential equations methods; flow, motion and registration; optimization theory and methods in imaging; machine learning in imaging; segmentation and labelling; restoration, reconstruction and interpolation; and inverse problems in imaging. 596 pp. Englisch.…

Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book constitutes the proceedings of the 8th International Conference on&nbspScale Space and Variational Methods in Computer Vision, SSVM 2021, which took place during May 16-20, 2021. The conference was planned to take place in Cabourg, France, but ch.…

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Scale Space and Partial Differential Equations Methods.- Scale-covariant and Scale-invariant Gaussian Derivative Networks.- Quantisation Scale-Spaces.- Equivariant Deep Learning via Morphological and Linear Scale Space PDEs on the Space of Positions and Orientations.- Nonlinear Spectral Processing of Shapes via Zero-homogeneous Flows.- Total-Variation Mode Decomposition.- Fast Morphological Dilation and Erosion for Grey Scale Images Using the Fourier Transform.- Diffusion, Pre-Smoothing and Gradient Descent.- Local Culprits of Shape Complexity.- Extension of Mathematical Morphology in Riemannian Spaces.- Flow, Motion and Registration.- Multiscale Registration.- Challenges for Optical Flow Estimates in Elastography.- An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation.- Low-rank Registration of Images Captured Under Unknown, Varying Lighting.- Towards Efficient Time Stepping for Numerical Shape Correspondence.- First Order Locally Orderless Registration.- Optimization Theory and Methods in Imaging.- First Order Geometric Multilevel Optimization For Discrete Tomography.- Bregman Proximal Gradient Algorithms for Deep Matrix Factorization.- Hessian Initialization Strategies for L-BFGS Solving Non-linear Inverse Problems.- Inverse Scale Space Iterations for Non-Convex Variational Problems Using Functional Lifting.- A Scaled and Adaptive FISTA Algorithm for Signal-dependent Sparse Image Super-resolution Problems.- Convergence Properties of a Randomized Primal-Dual Algorithm with Applications to Parallel MRI.- Machine Learning in Imaging.- Wasserstein Generative Models for Patch-based Texture Synthesis.- Sketched Learning for Image Denoising.- Translating Numerical Concepts for PDEs into Neural Architectures.- CLIP: Cheap Lipschitz Training of Neural Networks.- Variational Models for Signal Processing with Graph Neural Networks.- Synthetic Imagesas a Regularity Prior for Image Restoration Neural Networks.- Geometric Deformation on Objects: Unsupervised Image Manipulation via Conjugation.- Learning Local Regularization for Variational Image Restoration.- Segmentation and Labelling.- On the Correspondence between Replicator Dynamics and Assignment Flows.- Learning Linear Assignment Flows for Image Labeling via Exponential Integration.- On the Geometric Mechanics of Assignment Flows for Metric Data Labeling.- A Deep Image Prior Learning Algorithm for Joint Selective Segmentation and Registration.- Restoration, Reconstruction and Interpolation.- Inpainting-based Video Compression in FullHD.- Sparsity-aided Variational Mesh Restoration.- Lossless PDE-based Compression of 3D Medical Images.- Splines for Image Metamorphosis.- Residual Whiteness Principle for Automatic Parameter Selection in `2-`2 Image Super-resolution Problems.- Inverse Problems in Imaging.- Total Deep Variation for Noisy Exit Wave Reconstruction in Transmission Electron Microscopy.- GMM-based Simultaneous Reconstruction and Segmentation in X-ray CT application.- Phase Retrieval via Polarization in Dynamical Sampling.- Invertible Neural Networks versus MCMC for Posterior Reconstruction in Grazing Incidence X-Ray Fluorescence.- Adversarially Learned Iterative Reconstruction for Imaging Inverse Problems.- Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems.- Multi-frame Super-resolution from Noisy Data.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 596 pp. Englisch.…

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