Scale Space and Variational Methods in Computer Vision
portes grátis
Scale Space and Variational Methods in Computer Vision
9th International Conference, SSVM 2023, Santa Margherita di Pula, Italy, May 21-25, 2023, Proceedings
Donatelli, Marco; Morigi, Serena; Santacesaria, Matteo; Calatroni, Luca; Prato, Marco
Springer International Publishing AG
05/2023
759
Mole
Inglês
9783031319747
15 a 20 dias
Descrição não disponível.
?Inverse Problems in Imaging.- Explicit Diffusion of Gaussian Mixture Model Based Image Priors.- Efficient Neural Generation of 4K Masks for Homogeneous Diffusion Inpainting.- Theoretical Foundations for Pseudo-Inversion of Nonlinear Operators.- A Frame Decomposition of the Funk-Radon Transform.- Prony-Based Super-Resolution Phase Retrieval of Sparse, Multidimensional Signals.- Limited Electrodes Models in Electrical Impedance Tomography Reconstruction.- On Trainable Multiplicative Noise Removal Models.- Surface Reconstruction from 2D Noisy Point Cloud Data using Directional G-norm.- Regularized Material Decomposition for K-Edge Separation in Hyperspectral Computed Tomography.- Quaternary Image Decomposition with Cross-Correlation-Based Multi-Parameter Selection.- Machine and Deep Learning in Imaging.- EmNeF: Neural Fields for Embedded Variational Problems in Imaging.- GenHarris-ResNet: A Rotation Invariant Neural Network Based on Elementary Symmetric Polynomials.- Compressive Learning of Deep Regularization for Denoising.- Graph Laplacian and Neural Networks for Inverse Problems in Imaging: graphLaNet.- Learning Posterior Distributions in Underdetermined Inverse Problems.- Proximal Residual Flows for Bayesian Inverse Problems.- A Model Is Worth Tens of Thousands of Examples.- Resolution-Invariant Image Classification Based on Fourier Neural Operators.- Graph Laplacian for Semi-Supervised Learning.- A Geometrically Aware Auto-Encoder for Multi-Texture Synthesis.- Fast Marching Energy CNN.- Deep Accurate Solver for the Geodesic Problem.- Deep Image Prior Regularized by Coupled Total Variation for Image Colorization.- Hybrid Training of Denoising Networks to Improve the Texture Acutance of Digital Cameras.- Latent-Space Disentanglement with Untrained Generator Networks for the Isolation of Different Motion Types in Video Data.- Natural Numerical Networks on Directed Graphs in Satellite Image Classification.- Piece-Wise Constant Image Segmentation with a Deep Image PriorApproach.- On the Inclusion of Topological Requirements in CNNs for Semantic Segmentation Applied to Radiotherapy.- Optimization for Imaging: Theory and Methods.- A Relaxed Proximal Gradient Descent Algorithm for Convergent Plug-and-Play with Proximal Denoiser.- Off-the-Grid Charge Algorithm for Curve Reconstruction in Inverse Problems.- Convergence Guarantees of Overparametrized Wide Deep Inverse Prior.- On the Remarkable Efficiency of SMART.- Wasserstein Gradient Flows of the Discrepancy with Distance Kernel on the Line.- A Quasi-Newton Primal-Dual Algorithm with Line Search.- Stochastic Gradient Descent for Linear Inverse Problems in Variable Exponent Lebesgue Spaces.- An Efficient Line Search for Sparse Reconstruction.- Learned Discretization Schemes for the Second-Order Total Generalized Variation.- Fluctuation-Based Deconvolution in Fluorescence Microscopy Using Plug-and-Play Denoisers.- Segmenting MR Images Through Texture Extraction and Multiplicative Components Optimization.- Scale Space, PDEs, Flow, Motion and Registration.- Geodesic Tracking of Retinal Vascular Trees with Optical and TV-Flow Enhancement in SE(2).- Geometric Adaptations of PDE-G-CNNs.- The Variational Approach to the Flow of Sobolev-Diffeomorphisms Model.- Image Comparison and Scaling via Nonlinear Elasticity.- Learning Differential Invariants of Planar Curves.- Diffusion-Shock Inpainting.- Generalised Scale-Space Properties for Probabilistic Diffusion Models.- Gromov-Wasserstein Transfer Operators.- Optimal Transport Between GMM for Multiscale Texture Synthesis.- Asymptotic Result for a Decoupled Nonlinear Elasticity-Based Multiscale Registration Model.- Image Blending with Osmosis.- ?-Pixels for Hierarchical Analysis of Digital Objects.- Hypergraph p-Laplacians, Scale Spaces, and Information Flow in Networks.- On Photometric Stereo in the Presence of a Refractive Interface.- Multi-View Normal Estimation - Application to Slanted Plane-Sweeping.- Partial Shape Similarity by Multi-Metric Hamiltonian Spectra Matching.- Modeling Large-Scale Joint Distributions and Inference by RandomizedAssignment.- Quantum State Assignment Flows.
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image processing;mathematical imaging;computer vision;variational methods;partial differential equations;optimization;inverse problems;machine learning
?Inverse Problems in Imaging.- Explicit Diffusion of Gaussian Mixture Model Based Image Priors.- Efficient Neural Generation of 4K Masks for Homogeneous Diffusion Inpainting.- Theoretical Foundations for Pseudo-Inversion of Nonlinear Operators.- A Frame Decomposition of the Funk-Radon Transform.- Prony-Based Super-Resolution Phase Retrieval of Sparse, Multidimensional Signals.- Limited Electrodes Models in Electrical Impedance Tomography Reconstruction.- On Trainable Multiplicative Noise Removal Models.- Surface Reconstruction from 2D Noisy Point Cloud Data using Directional G-norm.- Regularized Material Decomposition for K-Edge Separation in Hyperspectral Computed Tomography.- Quaternary Image Decomposition with Cross-Correlation-Based Multi-Parameter Selection.- Machine and Deep Learning in Imaging.- EmNeF: Neural Fields for Embedded Variational Problems in Imaging.- GenHarris-ResNet: A Rotation Invariant Neural Network Based on Elementary Symmetric Polynomials.- Compressive Learning of Deep Regularization for Denoising.- Graph Laplacian and Neural Networks for Inverse Problems in Imaging: graphLaNet.- Learning Posterior Distributions in Underdetermined Inverse Problems.- Proximal Residual Flows for Bayesian Inverse Problems.- A Model Is Worth Tens of Thousands of Examples.- Resolution-Invariant Image Classification Based on Fourier Neural Operators.- Graph Laplacian for Semi-Supervised Learning.- A Geometrically Aware Auto-Encoder for Multi-Texture Synthesis.- Fast Marching Energy CNN.- Deep Accurate Solver for the Geodesic Problem.- Deep Image Prior Regularized by Coupled Total Variation for Image Colorization.- Hybrid Training of Denoising Networks to Improve the Texture Acutance of Digital Cameras.- Latent-Space Disentanglement with Untrained Generator Networks for the Isolation of Different Motion Types in Video Data.- Natural Numerical Networks on Directed Graphs in Satellite Image Classification.- Piece-Wise Constant Image Segmentation with a Deep Image PriorApproach.- On the Inclusion of Topological Requirements in CNNs for Semantic Segmentation Applied to Radiotherapy.- Optimization for Imaging: Theory and Methods.- A Relaxed Proximal Gradient Descent Algorithm for Convergent Plug-and-Play with Proximal Denoiser.- Off-the-Grid Charge Algorithm for Curve Reconstruction in Inverse Problems.- Convergence Guarantees of Overparametrized Wide Deep Inverse Prior.- On the Remarkable Efficiency of SMART.- Wasserstein Gradient Flows of the Discrepancy with Distance Kernel on the Line.- A Quasi-Newton Primal-Dual Algorithm with Line Search.- Stochastic Gradient Descent for Linear Inverse Problems in Variable Exponent Lebesgue Spaces.- An Efficient Line Search for Sparse Reconstruction.- Learned Discretization Schemes for the Second-Order Total Generalized Variation.- Fluctuation-Based Deconvolution in Fluorescence Microscopy Using Plug-and-Play Denoisers.- Segmenting MR Images Through Texture Extraction and Multiplicative Components Optimization.- Scale Space, PDEs, Flow, Motion and Registration.- Geodesic Tracking of Retinal Vascular Trees with Optical and TV-Flow Enhancement in SE(2).- Geometric Adaptations of PDE-G-CNNs.- The Variational Approach to the Flow of Sobolev-Diffeomorphisms Model.- Image Comparison and Scaling via Nonlinear Elasticity.- Learning Differential Invariants of Planar Curves.- Diffusion-Shock Inpainting.- Generalised Scale-Space Properties for Probabilistic Diffusion Models.- Gromov-Wasserstein Transfer Operators.- Optimal Transport Between GMM for Multiscale Texture Synthesis.- Asymptotic Result for a Decoupled Nonlinear Elasticity-Based Multiscale Registration Model.- Image Blending with Osmosis.- ?-Pixels for Hierarchical Analysis of Digital Objects.- Hypergraph p-Laplacians, Scale Spaces, and Information Flow in Networks.- On Photometric Stereo in the Presence of a Refractive Interface.- Multi-View Normal Estimation - Application to Slanted Plane-Sweeping.- Partial Shape Similarity by Multi-Metric Hamiltonian Spectra Matching.- Modeling Large-Scale Joint Distributions and Inference by RandomizedAssignment.- Quantum State Assignment Flows.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
