03035nam 22006495 450 991033784690332120251113181321.03-030-22368-X10.1007/978-3-030-22368-7(CKB)4100000008493462(DE-He213)978-3-030-22368-7(MiAaPQ)EBC5921663(PPN)254396240(EXLCZ)99410000000849346220190604d2019 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierScale Space and Variational Methods in Computer Vision 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 – July 4, 2019, Proceedings /edited by Jan Lellmann, Martin Burger, Jan Modersitzki1st ed. 2019.Cham :Springer International Publishing :Imprint: Springer,2019.1 online resource (XVII, 574 p. 302 illus., 153 illus. in color.) Image Processing, Computer Vision, Pattern Recognition, and Graphics,3004-9954 ;11603Includes index.3-030-22367-1 This book constitutes the proceedings of the 7th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2019, held in Hofgeismar, Germany, in June/July 2019. The 44 papers included in this volume were carefully reviewed and selected for inclusion in this book. They were organized in topical sections named: 3D vision and feature analysis; inpainting, interpolation and compression; inverse problems in imaging; optimization methods in imaging; PDEs and level-set methods; registration and reconstruction; scale-space methods; segmentation and labeling; and variational methods. .Image Processing, Computer Vision, Pattern Recognition, and Graphics,3004-9954 ;11603Computer visionNumerical analysisComputer scienceMathematicsArtificial intelligenceComputer VisionNumerical AnalysisMathematical Applications in Computer ScienceArtificial IntelligenceComputer vision.Numerical analysis.Computer scienceMathematics.Artificial intelligence.Computer Vision.Numerical Analysis.Mathematical Applications in Computer Science.Artificial Intelligence.006.37006.6Lellmann Janedthttp://id.loc.gov/vocabulary/relators/edtBurger Martinedthttp://id.loc.gov/vocabulary/relators/edtModersitzki Janedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910337846903321Scale Space and Variational Methods in Computer Vision4381134UNINA