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[null,"1.","Record Nr.",null,"UNISALENTO991001288399707536"]
[null,null,"Autore",null,"Crawford, A."]
[null,null,"Titolo",null,"Technique des ultrasons / A. Crawford"]
[null,null,"Pubbl/distr/stampa",null,"Paris : Dunod, 1959"]
[null,null,"Descrizione fisica",null,"1 v."]
[null,null,"Classificazione",null,"53.0.61"]
[{"$nulls":4},"53.7.2"]
[null,null,"Lingua di pubblicazione",null,"Francese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9910725100603321"]
[null,null,"Titolo",null,"Scale Space and Variational Methods in Computer Vision : 9th International Conference, SSVM 2023, Santa Margherita di Pula, Italy, May 21–25, 2023, Proceedings / / edited by Luca Calatroni, Marco Donatelli, Serena Morigi, Marco Prato, Matteo Santacesaria"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"9783031319754"]
[{"$nulls":4},"9783031319747"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (767 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science, , 1611-3349 ; ; 14009"]
[null,null,"Disciplina",null,"929.605"]
[null,null,"Soggetti",null,"Computer vision"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Social sciences - Data processing"]
[{"$nulls":4},"Machine learning"]
[{"$nulls":4},"Computer science - Mathematics"]
[{"$nulls":4},"Pattern recognition systems"]
[{"$nulls":4},"Computer Vision"]
[{"$nulls":4},"Computer Communication Networks"]
[{"$nulls":4},"Computer Application in Social and Behavioral Sciences"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Mathematics of Computing"]
[{"$nulls":4},"Automated Pattern Recognition"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Inverse Problems in Imaging -- Explicit Diffusion of Gaussian Mixture Model Based Image Priors -- Efficient Neural Generation of 4K Masks for Homogeneous Diffusion Inpainting -- Theoretical Foundations for Pseudo-Inversion of Nonlinear Operators -- A Frame Decomposition of the Funk-Radon Transform -- Prony-Based Super-Resolution Phase Retrieval of Sparse, Multidimensional Signals -- Limited Electrodes Models in Electrical Impedance Tomography Reconstruction -- On Trainable Multiplicative Noise Removal Models -- Surface Reconstruction from 2D Noisy Point Cloud Data using Directional G-norm -- Regularized Material Decomposition for K-Edge Separation in "]
[{"$nulls":4},"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 -- α-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 Randomized Assignment -- Quantum State Assignment Flows."]
[null,null,null,"Sommario/riassunto","This book constitutes the proceedings of the 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, which took place in Santa Margherita di Pula, Italy, "]
[{"$nulls":4},"in May 2023. The 57 papers presented in this volume were carefully reviewed and selected from 72 submissions. They were organized in topical sections as follows: Inverse Problems in Imaging; Machine and Deep Learning in Imaging; Optimization for Imaging: Theory and Methods; Scale Space, PDEs, Flow, Motion and Registration."]