Scale space and variational methods in computer vision : 8th international conference, SSVM 2021, Virtual Event, May 16-20, 2021, proceedings / / Abderrahim Elmoataz [and four others], editors

• Record Nr.: UNISA996464421103316
• Pubbl/distr/stampa: Cham, Switzerland : , : Springer, , [2021]; ©2021
• ISBN: 3-030-75549-5
• Descrizione fisica: 1 online resource (584 pages)
• Collana: Lecture Notes in Computer Science ; ; 12679
• Disciplina: 006.37
• Soggetti: Computer vision
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Intro -- Preface -- Organization -- Contents -- Scale Space and Partial Differential Equations Methods -- Scale-Covariant and Scale-Invariant Gaussian Derivative Networks -- 1 Introduction -- 2 Relations to Previous Work -- 3 Gaussian Derivative Networks -- 3.1 Provable Scale Covariance -- 4 Experiments with a Single-Scale-Channel Network -- 4.1 Discrete Implementation -- 5 Experiments with a Multi-Scale-Channel Network -- 5.1 Scale Selection Properties -- 6 Summary and Discussion -- References -- Quantisation Scale-Spaces -- 1 Introduction -- 2 Quantisation Scale-Spaces -- 2.1 Scale-Space Properties -- 3 Relations to Sparsification Scale-Spaces -- 4 Applications to Quantisation and Compression -- 4.1 Uncommitted and Committed Quantisation -- 4.2 Inpainting-Based Compression -- 5 Conclusions -- References -- Equivariant Deep Learning via Morphological and Linear Scale Space PDEs on the Space of Positions and Orientations -- 1 Introduction -- 2 Design of PDE-Based Equivariant Neural Network -- 2.1 The Lifting Layer: Extending the Image Domain from Rd to Md -- 2.2 PDE Layers by Linear and Morphological Scale Spaces on Md -- 2.3 PDE-Based Deep Learning by G-CNNs on M2 -- 3 Linear and Morphological Kernel Implementation -- 3.1 Analytic Approximations of -Scale-Space Kernels on M2 -- 3.2 Analytic Approximations of -Dilation/Erosion Kernels on M2 -- 4 Experimental Observations and Analysis -- 5 Conclusion -- References ; -- Nonlinear Spectral Processing of Shapes via Zero-Homogeneous Flows -- 1 Introduction -- 2 Background -- 2.1 Differential Operators on Manifolds -- 2.2 Vectorial Total Variation -- 2.3 Laplacian-Based Flows -- 2.4 TV Mesh Processing -- 3 Proposed Methods -- 3.1 Naive Method: Unpaired Coordinate Spectral TV -- 3.2 Method 1 (M1): Shape Spectral TV -- 3.3 Method 2 (M2): Conformalized P-Laplace -- 3.4 Method 3 (M3): Directional Shape TV.; 4 Discussion and Conclusion -- References -- Total-Variation Mode Decomposition -- 1 Introduction -- 2 Preliminary -- 2.1 Dynamic Mode Decomposition (DMD) -- 2.2 Total Variation Spectral Decomposition -- 3 DMD of the TV Flow -- 3.1 Closed Form Solution -- 3.2 Flow Transitions and a Fast TV-flow Algorithm -- 3.3 Rescaled-DMD -- 3.4 Analysis of the Rescaled-DMD -- 4 Results and Conclusion -- References -- Fast Morphological Dilation and Erosion for Grey Scale Images Using the Fourier Transform -- 1 Introduction -- 2 Morphological Dilation and Erosion -- 3 Greyscale Dilation Discretisation with Convolution -- 3.1 Analytic Motivation of the Algorithm -- 3.2 Details on the Algorithm -- 4 Experiments -- 5 Conclusion -- References -- Diffusion, Pre-smoothing and Gradient Descent -- 1 Introduction -- 2 Integrability Analysis of Diffusion with Pre-smoothing -- 3 Alternatives -- 4 Experiments -- 5 Summary -- References -- Local Culprits of Shape Complexity -- 1 Introduction -- 2 Method -- 3 Illustrative Experiments -- 4 Summary and Future Work -- References -- Extension of Mathematical Morphology in Riemannian Spaces -- 1 Introduction -- 2 Background on MM and HLO Formulas -- 2.1 Basic Morphological Operators, Scale-Spaces and PDEs -- 2.2 HLO Formulas and Hamilton-Jacobi Equations -- 3 HLO Formulas in Riemannian Manifolds -- 3.1 Viscosity Solutions in Riemannian Manifolds -- 3.2 Example and Some Properties -- 4 Conclusion -- References -- Flow, Motion and Registration -- Multiscale Registration -- 1 Introduction -- 2 Mathematical Modelling -- 2.1 Depiction of the Model -- 2.2 Theoretical Results -- 3 Numerical Resolution -- 4 Numerical Experiments -- 5 Conclusion -- References -- Challenges for Optical Flow Estimates in Elastography -- 1 Introduction and Motivation -- 2 Displacement Field Estimation via Optical Flow -- 2.1 Speckle Tracking.; 2.2 Boundary Conditions -- 2.3 Homogeneous Background Information -- 3 The Elastographic Optical Flow Method -- 4 Numerical Results -- 4.1 Simulated Data -- 4.2 Experimental Data -- 5 Summary -- References -- An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation -- 1 Introduction -- 2 Variational Optical Flow -- 3 Regularisation with Isotropic Selection Scheme -- 4 Regularisation with Anisotropic Selection Scheme -- 5 Minimisation -- 6 Evaluation -- 6.1 Stand-Alone Approach -- 6.2 Refinement Approach -- 7 Conclusion -- References -- Low-Rank Registration of Images Captured Under Unknown, Varying Lighting -- 1 Introduction -- 2 Related Works -- 3 Low-Rank Registration of Photometric Stereo Images -- 3.1 Displacement Parameterization -- 3.2 Low-Rank Formulation and Convex Relaxation -- 4 Augmented Lagrangian Framework -- 4.1 Splitting -- 4.2 Updating the Corrected Observation Matrix A -- 4.3 Updating the Error Vector e -- 4.4 Updating the Displacement Coefficients -- 5 Implementation -- 5.1 Multi-scale Scheme -- 5.2 Using a Sparse Subset of Pixels -- 5.3 Empirical Evaluation -- 6 Conclusions and Perspectives -- References -- Towards Efficient Time Stepping for Numerical Shape Correspondence -- 1 Introduction -- 2 Modelling of the Shape Correspondence Framework -- 3 Spatial Discretisation -- 4 Time Discretisation -- 5 Experiments -- 6 Conclusion and Further Work -- ; References -- First Order Locally Orderless Registration -- 1 Introduction -- 2 Related Work -- 3 Background on Locally Orderless Image Information -- 3.1 Notations -- 3.2 Lebesgue Integration and Histograms -- 3.3 LOI and LOR Framework -- 4 Extension of LOI and LOR to Higher Information -- 4.1 First Order Locally Orderless Registration (FLOR) -- 4.2 First Order Deformation Model -- 4.3 Registration Objectives and Deformations.; 4.4 Implementation -- 5 Experiments and Results -- 5.1 The Similarity Properties -- 5.2 Non-rigid Registration -- 5.3 Discussion and Limitations -- 6 Conclusion -- References -- Optimization Theory and Methods in Imaging -- First-Order Geometric Multilevel Optimization for Discrete Tomography -- 1 Introduction -- 2 Multilevel Optimization in Euclidean Space -- 3 Geometric Approach -- 4 Experiments -- 5 Conclusion -- References -- Bregman Proximal Gradient Algorithms for Deep Matrix Factorization -- 1 Introduction -- 2 Related Work -- 3 Bregman Proximal Minimization -- 3.1 Bregman Proximal Gradient -- 4 BPG for Deep Matrix Factorization -- 4.1 Smooth Adaptable Property for DLNN -- 4.2 Closed Form Updates for BPG -- 4.3 Global Convergence of BPG for Regularized DLNN -- 4.4 Discussion of BPG Variants -- 5 Experiments -- 6 Conclusion -- References -- Hessian Initialization Strategies for -BFGS Solving Non-linear Inverse Problems -- 1 Introduction -- 2 Proposed Hessian Initialization Strategy and Algorithm -- 3 Numerical Experiments and Results -- 3.1 Quadratic Problem -- 3.2 Image Registration -- 4 Conclusion -- References -- Inverse Scale Space Iterations for Non-convex Variational Problems Using Functional Lifting -- 1 Motivation and Introduction -- 2 Sublabel-Accurate Lifting Approach -- 3 Equivalency of the Lifted Bregman Iteration -- 4 Numerical Discussion and Results -- References -- A Scaled and Adaptive FISTA Algorithm for Signal-Dependent Sparse Image Super-Resolution Problems -- 1 Introduction -- 2 Scaled and Adaptive FISTA -- 3 Application to Sparse Weighted Models for Super-Resolution Microscopy -- 3.1 Sparse Image Super-Resolution with Poisson Data -- 3.2 Solving (8) Efficiently: IRL1 Algorithm with S-FISTA Solver -- 4 Numerical Results -- 4.1 Weighted-2-1 Minimization -- 4.2 Weighted-CEL0 Minimization -- 5 Conclusions -- References.; Convergence Properties of a Randomized Primal-Dual Algorithm with Applications to Parallel MRI -- 1 Introduction -- 2 Algorithm -- 3 Main Result -- 4 Sketch of the Proof -- 5 Proof of Convergence -- 5.1 Proof of Proposition1 i) -- 5.2 Proof of Proposition1 ii)-iii) -- 5.3 Proof of Proposition 1 iv) -- 5.4 Proof of Proposition2 -- 6 Relation to Other Work -- 6.1 Chambolle et al. (2018) -- 6.2 Combettes and Pesquet (2014) -- 6.3 Alacaoglu et al. (2019) -- 7 Numerical Examples -- 8 Conclusions -- References -- Machine Learning in Imaging -- Wasserstein Generative Models for Patch-Based Texture Synthesis -- 1 Introduction -- 2 Gradient of Optimal Transport -- 3 Image Optimization -- 3.1 Mono-Scale Texture Synthesis Algorithm -- 3.2 Multi-scale Texture Synthesis -- 3.3 Experiments -- 4 Training a Convolutional Generative Network -- 4.1 Proposed Algorithm for Semi-discrete Formulation -- 4.2 Experimental Results and Discussions -- 4.3 Evaluation of Texture Synthesis Methods -- References -- Sketched Learning for Image Denoising -- 1 Introduction -- 2 Model Estimation and Denoising with EPLL -- 2.1 Denoising with EPLL -- 2.2 EM -- 3 Compressive GMM Learning from Large Image Patches Database with Sketches -- 3.1 Compressive Mixture Estimation -- 3.2 Design of Sketching Operator: Randomly Sampling the Characteristic Function -- 3.3 Extension to Low Rank Covariances -- 3.4 An Algorithm for Patch Prior Learning from Sketch: LR-COMP (Low Rank Continuous ; Orthogonal Matching Pursuit) -- 4 Results and Analysis -- 4.1 Experiments with Synthetic Data -- 4.2 Results with Real Images -- 5 Conclusion -- References -- Translating Numerical Concepts for PDEs into Neural Architectures -- 1 Introduction -- 2 Networks from Algorithms for Evolution Equations -- 2.1 Generalised Nonlinear Diffusion -- 2.2 Residual Networks -- 2.3 Expressing Explicit Schemes as Residual Networks.; 2.4 Criteria for Well-Posed and Stable Residual Networks.

The baiting of the Popes bull. Or an vnmasking of the mystery of iniquity, folded vp in a most pernitious breeue or bull, sent from the Pope lately into England, to cawse a rent therein, for his reentry [[electronic resource] ] : With an advertisement to the Kings seduced subiects. By H.B

• Record Nr.: UNISA996395625603316
• Autore: Burton Henry <1578-1648.>
• Pubbl/distr/stampa: Imprinted at London, : By W[illiam] I[ones, Augustine Mathewes, John Jaggard? and others?] for Michaell Sparke, 1627
• Descrizione fisica: [52], 95, [1] p
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: H.B. = Henry Burton.; Reprints and answers the letter sent by Pope Urban VIII dated 30 May 1626.; Printer's name from STC. "pi² , M-N⁴ are the same setting as 4137, and 2[par.]⁴, 2*⁴. [sec.]⁴ are reimposed from 4137. A. Mathewes pr[inted]. at least [par.]⁴, a⁴; I. Jaggard prob[ably]. pr[inted]. at least A-B⁴, and other printers may have been involved"--STC. Copies may show a mixture of sheets with STC 4137.; The first leaf contains verses referring to the title-page woodcut.; In this edition the dedication to Buckingham begins on leaf a1r.; Folger Library copy identified as STC 4137a, and British Library copy as 4137, on UMI microfilm.; Reproductions of the originals in the Folger Shakespeare Library and the British Library.; Appears at reel 587 (Folger Shakespeare Library copy) and at reel 707 (British Library copy).
• Sommario/riassunto: eebo-0216

Rechtliche Beurteilung von Mikrotransaktionen und Lootboxen

• Record Nr.: UNINA9910637768403321
• Autore: Busch Max
• Pubbl/distr/stampa: Universitätsverlag Göttingen, 2022
• Soggetti: Law
• Lingua di pubblicazione: Tedesco
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Sommario/riassunto: The purchase of additional items in videogames, also called ‘Microtransactions’, has recently grown to become one of the dominating methods of monetization in the games industry. However, many versions of these monetization schemes face severe backlash because it appears that the ways to monetize games are increasingly influencing the contents of the medium and that those games are purposefully designed to bring vulnerable players to spend more money than they meant to. In this thesis, those points of criticism were taken into consideration and as a starting point to explore the legality of these kinds of monetization schemes from a legal standpoint. This was done with regards to the Unfair Competition Law, Youth Protection regulation and general civil law. Also, the chance-based variant of microtransactions, the so called ‘Lootboxes’, have been examined with regard to their ; legality under gambling regulations.