Bubba tatiana (12 Ergebnisse)

Taschenbuch. Zustand: Neu. Scale Space and Variational Methods in Computer Vision | 10th International Conference, SSVM 2025, Dartington, UK, May 18-22, 2025, Proceedings, Part II | Tatiana A. Bubba (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xvii | Englisch | 2025 | Springer | EAN 9783031923685 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Taschenbuch. Zustand: Neu. Scale Space and Variational Methods in Computer Vision | 10th International Conference, SSVM 2025, Dartington, UK, May 18-22, 2025, Proceedings, Part I | Tatiana A. Bubba (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xvii | Englisch | 2025 | Springer | EAN 9783031923654 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

Paperback. Zustand: Brand New. 400 pages. 9.26x6.11x9.21 inches. In Stock.

Paperback. Zustand: Brand New. 400 pages. 9.26x6.11x9.21 inches. In Stock.

Hardcover. Zustand: New. The series is devoted to the publication of high-level monographs, surveys and proceedings which cover the whole spectrum of computational and applied mathematics. The books of this series are addressed to both specialists and advanced students. .

Buch. Zustand: Neu. Data-driven Models in Inverse Problems | Tatiana A. Bubba | Buch | VIII | Englisch | 2024 | De Gruyter | EAN 9783111250038 | Verantwortliche Person für die EU: Walter de Gruyter GmbH, De Gruyter GmbH, Genthiner Str. 13, 10785 Berlin, productsafety[at]degruyterbrill[dot]com | Anbieter: preigu.…

Buch. Zustand: Neu. Neuware - Advances in learning-based methods are revolutionizing several fields in applied mathematics, including inverse problems, resulting in a major paradigm shift towards data-driven approaches. This volume, which is inspired by this cutting-edge area of research, brings together contributors from the inverse problem community and shows how to successfully combine model- and data-driven approaches to gain insight into practical and theoretical issues.…

Taschenbuch. Zustand: Neu. Advanced Techniques in Optimization for Machine Learning and Imaging | Alessandro Benfenati (u. a.) | Taschenbuch | Springer INdAM Series | x | Englisch | 2025 | Springer | EAN 9789819767717 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In recent years, non-linear optimization has had a crucial role in the development of modern techniques at the interface of machine learning and imaging. The present book is a collection of recent contributions in the field of optimization, either revisiting consolidated ideas to provide formal theoretical guarantees or providing comparative numerical studies for challenging inverse problems in imaging. The work of these papers originated in the INdAM Workshop 'Advanced Techniques in Optimization for Machine learning and Imaging' held in Roma, Italy, on June 20-24, 2022.The covered topics include non-smooth optimisation techniques for model-driven variational regularization, fixed-point continuation algorithms and their theoretical analysis for selection strategies of the regularization parameter for linear inverse problems in imaging, different perspectives on Support Vector Machines trained via Majorization-Minimization methods, generalization of Bayesian statistical frameworks to imaging problems, and creation of benchmark datasets for testing new methods and algorithms.…

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In recent years, non-linear optimization has had a crucial role in the development of modern techniques at the interface of machine learning and imaging. The present book is a collection of recent contributions in the field of optimization, either revisiting consolidated ideas to provide formal theoretical guarantees or providing comparative numerical studies for challenging inverse problems in imaging. The work of these papers originated in the INdAM Workshop 'Advanced Techniques in Optimization for Machine learning and Imaging' held in Roma, Italy, on June 20-24, 2022.The covered topics include non-smooth optimisation techniques for model-driven variational regularization, fixed-point continuation algorithms and their theoretical analysis for selection strategies of the regularization parameter for linear inverse problems in imaging, different perspectives on Support Vector Machines trained via Majorization-Minimization methods, generalization of Bayesian statistical frameworks to imaging problems, and creation of benchmark datasets for testing new methods and algorithms.…