Isbn: 9783030755485 - scale space and variational methods in computer vision: 8th international conference, ssvm 2021, virtual event, may 16–20, 2021, proceedings: 12679 (18 risultati)

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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.…

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.…

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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.…

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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.…

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.…