Scale Space and Variational Methods in Computer Vision [electronic resource] : 6th International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 2017, Proceedings / edited by François Lauze, Yiqiu Dong, Anders Bjorholm Dahl.
Вид матеріалу:
Текст Серія: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 10302Публікація: Cham : Springer International Publishing : Imprint: Springer, 2017Видання: 1st ed. 2017Опис: XV, 708 p. 244 illus. online resourceТип вмісту: - text
- computer
- online resource
- 9783319587714
- Optical data processing
- Computer graphics
- Pattern recognition
- Algorithms
- Application software
- Computers
- Image Processing and Computer Vision
- Computer Graphics
- Pattern Recognition
- Algorithm Analysis and Problem Complexity
- Information Systems Applications (incl. Internet)
- Computation by Abstract Devices
- 006.6 23
- 006.37 23
- TA1630-1650
ЕКнига
Списки з цим бібзаписом:
Springer Ebooks (till 2020 - Open Access)+(2017 Network Access))
|
Springer Ebooks (2017 Network Access))
Scale Space and PDE Methods -- Restoration and Reconstruction -- Tomographic Reconstruction -- Segmentation -- Convex and Non-Convex Modeling and Optimization in Imaging -- Optical Flow, Motion Estimation and Registration -- 3D Vision.
This book constitutes the refereed proceedings of the 6th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2017, held in Kolding, Denmark, in June 2017. The 55 revised full papers presented were carefully reviewed and selected from 77 submissions. The papers are organized in the following topical sections: Scale Space and PDE Methods; Restoration and Reconstruction; Tomographic Reconstruction; Segmentation; Convex and Non-Convex Modeling and Optimization in Imaging; Optical Flow, Motion Estimation and Registration; 3D Vision.
Available to subscribing member institutions only. Доступно лише організаціям членам підписки.
Online access from local network of NaUOA.
Online access with authorization at https://link.springer.com/
Онлайн-доступ з локальної мережі НаУОА.
Онлайн доступ з авторизацією на https://link.springer.com/
Немає коментарів для цієї одиниці.