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Scale Space and Variational Methods in Computer Vision : 10th International Conference, SSVM 2025, Dartington, UK, May 18–22, 2025, Proceedings, Part I / edited by Tatiana A. Bubba, Romina Gaburro, Silvia Gazzola, Kostas Papafitsoros, Marcelo Pereyra, Carola-Bibiane Schönlieb.
Springer Nature - Springer Computer Science (R0) eBooks 2025 English International Available online
View online- Format:
- Book
- Series:
- Lecture Notes in Computer Science, 1611-3349 ; 15667
- Language:
- English
- Subjects (All):
- Image processing.
- Computer networks.
- Application software.
- Machine learning.
- Computer science--Mathematics.
- Computer science.
- Image processing--Digital techniques.
- Computer vision.
- Image Processing.
- Computer Communication Networks.
- Computer and Information Systems Applications.
- Machine Learning.
- Mathematics of Computing.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Local Subjects:
- Image Processing.
- Computer Communication Networks.
- Computer and Information Systems Applications.
- Machine Learning.
- Mathematics of Computing.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Physical Description:
- 1 online resource (XVII, 415 p. 147 illus., 117 illus. in color.)
- Edition:
- 1st ed. 2025.
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
- Summary:
- The two-volume set LNCS 15667 and 15668 constitutes the proceedings of the 10th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2025, which took place in Dartington, UK, in May 2025. The total of 63 full papers accepted in the proceedings were carefully reviewed and selected from 81 submissions. They were organized in topical sections as follows: Part I: Inverse Problems in Imaging; machine and deep learning in imaging; Part II: Optimization for imaging: theory and methods; scale space, PDES, flow, motion and registration.
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 3-031-92366-9
- OCLC:
- 1524422782
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