Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2

Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2

Kimmel, Ron
Tai, Xue-Cheng

171,60 €(IVA inc.)

Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2, Volume 20 surveys the contemporary developments relating to the analysis and learning of images, shapes and forms, covering mathematical models and quick computational techniques. Chapter cover Alternating Diffusion: A Geometric Approach for Sensor Fusion, Generating Structured TV-based Priors and Associated Primal-dual Methods, Graph-based Optimization Approaches for Machine Learning, Uncertainty Quantification and Networks, Extrinsic Shape Analysis from Boundary Representations, Efficient Numerical Methods for Gradient Flows and Phase-field Models, Recent Advances in Denoising of Manifold-Valued Images, Optimal Registration of Images, Surfaces and Shapes, and much more. Covers contemporary developments relating to the analysis and learning of images, shapes and formsPresents mathematical models and quick computational techniques relating to the topicProvides broad coverage, with sample chapters presenting content on Alternating Diffusion and Generating Structured TV-based Priors and Associated Primal-dual Methods INDICE: 1. Alternating diffusion: a geometric approach for sensor fusion Ronen Talmon 2. Generating structured TV-based priors and associated primal-dual methods Michael Hintermueller 3. Graph-based optimization approaches for machine learning, uncertainty quantification and networks Andrea L. Bertozzi 4. Extrinsic shape analysis from boundary representations Justin Solomon 5. Efficient numerical methods for gradient flows and phase-field models Jie Shen 6. Recent Advances in Denoising of Manifold-Valued Images Gabriele Steidl 7. Optimal Registration of Images, Surfaces and Shapes Chen Ke 8. Finite Difference Methods for Approximating Total Variation Flow Joachim Weickert 9. Metric invariants of curves and surfaces Dan Raviv 10. Using Geodesics to find the global minimum of different kinds of active contours for Segmentation Laurent D. Cohen 11. Geometric PDEs on manifolds represented as point clouds and applications Hongkai Zhao 12. Operator-based representations for geometry processing Mirela Ben Chen 13. Variational time discretization of Riemannian splines Martin Rumpf 14. Survey of geometry inspired variational segmentation: interface model, curvature terms and fast computation Sung ha Kang and Xue-Cheng Tai 15. Recent developments for fast operator splitting algorithms for variational models Xue-Cheng Tai 16. Fast discrete algorithms for image segmentations Yuri Boykov 17. Metric Registration of Curves and Surfaces using Optimal Control Laurent Younes 18. Active Contour Methods on Arbitrary Graphs Based on Partial Differential Equations Petros Maragos 19. Lagrangian Methods for Composite Optimization Marc Teboulle and Shoham Sabach 20. Tightening continuous relaxations for MAP inference in discrete MRFs: A survey Nikos Paragios and Hariprasad Kannan

  • ISBN: 978-0-444-64140-3
  • Editorial: North Holland
  • Encuadernacion: Cartoné
  • Páginas: 525
  • Fecha Publicación: 01/10/2019
  • Nº Volúmenes: 1
  • Idioma: Inglés