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Scale 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 Modersitzki.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 11603
- Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11603
- Language:
- English
- Subjects (All):
- Computer vision.
- Numerical analysis.
- Computer science-Mathematics.
- Artificial intelligence.
- Computer Vision.
- Numerical Analysis.
- Mathematical Applications in Computer Science.
- Artificial Intelligence.
- Local Subjects:
- Computer Vision.
- Numerical Analysis.
- Mathematical Applications in Computer Science.
- Artificial Intelligence.
- Physical Description:
- 1 online resource (XVII, 574 pages) : 302 illustrations, 153 illustrations in color.
- Edition:
- 1st ed. 2019.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2019.
- System Details:
- text file PDF
- Summary:
- 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. .
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-22368-7
- 9783030223687
- Access Restriction:
- Restricted for use by site license.
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