Handbook Of Variational Methods For Nonlinear Geometric Data

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Handbook of Variational Methods for Nonlinear Geometric Data

Philipp Grohs,Martin Holler,Andreas Weinmann
Handbook of Variational Methods for Nonlinear Geometric Data Book PDF

Author : Philipp Grohs,Martin Holler,Andreas Weinmann
Publisher : Springer Nature
Page : 701 pages
File Size : 52,9 Mb
Release : 2020-04-03
Category : Mathematics
ISBN : 9783030313517

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Handbook of Variational Methods for Nonlinear Geometric Data by Philipp Grohs,Martin Holler,Andreas Weinmann Pdf

This book covers different, current research directions in the context of variational methods for non-linear geometric data. Each chapter is authored by leading experts in the respective discipline and provides an introduction, an overview and a description of the current state of the art. Non-linear geometric data arises in various applications in science and engineering. Examples of nonlinear data spaces are diverse and include, for instance, nonlinear spaces of matrices, spaces of curves, shapes as well as manifolds of probability measures. Applications can be found in biology, medicine, product engineering, geography and computer vision for instance. Variational methods on the other hand have evolved to being amongst the most powerful tools for applied mathematics. They involve techniques from various branches of mathematics such as statistics, modeling, optimization, numerical mathematics and analysis. The vast majority of research on variational methods, however, is focused on data in linear spaces. Variational methods for non-linear data is currently an emerging research topic. As a result, and since such methods involve various branches of mathematics, there is a plethora of different, recent approaches dealing with different aspects of variational methods for nonlinear geometric data. Research results are rather scattered and appear in journals of different mathematical communities. The main purpose of the book is to account for that by providing, for the first time, a comprehensive collection of different research directions and existing approaches in this context. It is organized in a way that leading researchers from the different fields provide an introductory overview of recent research directions in their respective discipline. As such, the book is a unique reference work for both newcomers in the field of variational methods for non-linear geometric data, as well as for established experts that aim at to exploit new research directions or collaborations. Chapter 9 of this book is available open access under a CC BY 4.0 license at link.springer.com.

Scale Space and Variational Methods in Computer Vision

Abderrahim Elmoataz,Jalal Fadili,Yvain Quéau,Julien Rabin,Loïc Simon
Scale Space and Variational Methods in Computer Vision Book PDF

Author : Abderrahim Elmoataz,Jalal Fadili,Yvain Quéau,Julien Rabin,Loïc Simon
Publisher : Springer Nature
Page : 584 pages
File Size : 42,9 Mb
Release : 2021-04-29
Category : Computers
ISBN : 9783030755492

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Scale Space and Variational Methods in Computer Vision by Abderrahim Elmoataz,Jalal Fadili,Yvain Quéau,Julien Rabin,Loïc Simon Pdf

This book constitutes the proceedings of the 8th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2021, which took place during May 16-20, 2021. The conference was planned to take place in Cabourg, France, but changed to an online format due to the COVID-19 pandemic. The 45 papers included in this volume were carefully reviewed and selected from a total of 64 submissions. They were organized in topical sections named as follows: scale space and partial differential equations methods; flow, motion and registration; optimization theory and methods in imaging; machine learning in imaging; segmentation and labelling; restoration, reconstruction and interpolation; and inverse problems in imaging.

Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging

Ke Chen,Carola-Bibiane Schönlieb,Xue-Cheng Tai,Laurent Younes
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging Book PDF

Author : Ke Chen,Carola-Bibiane Schönlieb,Xue-Cheng Tai,Laurent Younes
Publisher : Springer Nature
Page : 1981 pages
File Size : 42,5 Mb
Release : 2023-02-24
Category : Mathematics
ISBN : 9783030986612

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Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging by Ke Chen,Carola-Bibiane Schönlieb,Xue-Cheng Tai,Laurent Younes Pdf

This handbook gathers together the state of the art on mathematical models and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal solutions to a class of imaging and vision problems, and on effective algorithms, which are necessary for the methods to be translated to practical use in various applications. Viewing discrete images as data sampled from functional surfaces enables the use of advanced tools from calculus, functions and calculus of variations, and nonlinear optimization, and provides the basis of high-resolution imaging through geometry and variational models. Besides, optimization naturally connects traditional model-driven approaches to the emerging data-driven approaches of machine and deep learning. No other framework can provide comparable accuracy and precision to imaging and vision. Written by leading researchers in imaging and vision, the chapters in this handbook all start with gentle introductions, which make this work accessible to graduate students. For newcomers to the field, the book provides a comprehensive and fast-track introduction to the content, to save time and get on with tackling new and emerging challenges. For researchers, exposure to the state of the art of research works leads to an overall view of the entire field so as to guide new research directions and avoid pitfalls in moving the field forward and looking into the next decades of imaging and information services. This work can greatly benefit graduate students, researchers, and practitioners in imaging and vision; applied mathematicians; medical imagers; engineers; and computer scientists.

Riemannian Optimization and Its Applications

Hiroyuki Sato
Riemannian Optimization and Its Applications Book PDF

Author : Hiroyuki Sato
Publisher : Springer Nature
Page : 129 pages
File Size : 49,8 Mb
Release : 2021-02-17
Category : Technology & Engineering
ISBN : 9783030623913

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Riemannian Optimization and Its Applications by Hiroyuki Sato Pdf

This brief describes the basics of Riemannian optimization—optimization on Riemannian manifolds—introduces algorithms for Riemannian optimization problems, discusses the theoretical properties of these algorithms, and suggests possible applications of Riemannian optimization to problems in other fields. To provide the reader with a smooth introduction to Riemannian optimization, brief reviews of mathematical optimization in Euclidean spaces and Riemannian geometry are included. Riemannian optimization is then introduced by merging these concepts. In particular, the Euclidean and Riemannian conjugate gradient methods are discussed in detail. A brief review of recent developments in Riemannian optimization is also provided. Riemannian optimization methods are applicable to many problems in various fields. This brief discusses some important applications including the eigenvalue and singular value decompositions in numerical linear algebra, optimal model reduction in control engineering, and canonical correlation analysis in statistics.

Pattern Recognition

Zeynep Akata,Andreas Geiger,Torsten Sattler
Pattern Recognition Book PDF

Author : Zeynep Akata,Andreas Geiger,Torsten Sattler
Publisher : Springer Nature
Page : 504 pages
File Size : 42,8 Mb
Release : 2021-03-16
Category : Computers
ISBN : 9783030712785

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Pattern Recognition by Zeynep Akata,Andreas Geiger,Torsten Sattler Pdf

This book constitutes the refereed proceedings of the 42nd German Conference on Pattern Recognition, DAGM GCPR 2020, which took place during September 28 until October 1, 2020. The conference was planned to take place in Tübingen, Germany, but had to change to an online format due to the COVID-19 pandemic. The 34 papers presented in this volume were carefully reviewed and selected from a total of 89 submissions. They were organized in topical sections named: Normalizing Flow, Semantics, Physics, Camera Calibration and Computer Vision, Pattern Recognition, Machine Learning.

Scale Space and Variational Methods in Computer Vision

Luca Calatroni,Marco Donatelli,Serena Morigi,Marco Prato,Matteo Santacesaria
Scale Space and Variational Methods in Computer Vision Book PDF

Author : Luca Calatroni,Marco Donatelli,Serena Morigi,Marco Prato,Matteo Santacesaria
Publisher : Springer Nature
Page : 767 pages
File Size : 51,7 Mb
Release : 2023-05-09
Category : Computers
ISBN : 9783031319754

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Scale Space and Variational Methods in Computer Vision by Luca Calatroni,Marco Donatelli,Serena Morigi,Marco Prato,Matteo Santacesaria Pdf

This book constitutes the proceedings of the 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, which took place in Santa Margherita di Pula, Italy, in May 2023. The 57 papers presented in this volume were carefully reviewed and selected from 72 submissions. They were organized in topical sections as follows: Inverse Problems in Imaging; Machine and Deep Learning in Imaging; Optimization for Imaging: Theory and Methods; Scale Space, PDEs, Flow, Motion and Registration.

Geometric Science of Information

Frank Nielsen,Frédéric Barbaresco
Geometric Science of Information Book PDF

Author : Frank Nielsen,Frédéric Barbaresco
Publisher : Springer Nature
Page : 929 pages
File Size : 46,7 Mb
Release : 2021-07-14
Category : Computers
ISBN : 9783030802097

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Geometric Science of Information by Frank Nielsen,Frédéric Barbaresco Pdf

This book constitutes the proceedings of the 5th International Conference on Geometric Science of Information, GSI 2021, held in Paris, France, in July 2021. The 98 papers presented in this volume were carefully reviewed and selected from 125 submissions. They cover all the main topics and highlights in the domain of geometric science of information, including information geometry manifolds of structured data/information and their advanced applications. The papers are organized in the following topics: Probability and statistics on Riemannian Manifolds; sub-Riemannian geometry and neuromathematics; shapes spaces; geometry of quantum states; geometric and structure preserving discretizations; information geometry in physics; Lie group machine learning; geometric and symplectic methods for hydrodynamical models; harmonic analysis on Lie groups; statistical manifold and Hessian information geometry; geometric mechanics; deformed entropy, cross-entropy, and relative entropy; transformation information geometry; statistics, information and topology; geometric deep learning; topological and geometrical structures in neurosciences; computational information geometry; manifold and optimization; divergence statistics; optimal transport and learning; and geometric structures in thermodynamics and statistical physics.

Variational Methods in Nonlinear Analysis

Dimitrios C. Kravvaritis,Athanasios N. Yannacopoulos
Variational Methods in Nonlinear Analysis Book PDF

Author : Dimitrios C. Kravvaritis,Athanasios N. Yannacopoulos
Publisher : Walter de Gruyter GmbH & Co KG
Page : 499 pages
File Size : 40,7 Mb
Release : 2020-04-06
Category : Mathematics
ISBN : 9783110647389

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Variational Methods in Nonlinear Analysis by Dimitrios C. Kravvaritis,Athanasios N. Yannacopoulos Pdf

This well-thought-out book covers the fundamentals of nonlinear analysis, with a particular focus on variational methods and their applications. Starting from preliminaries in functional analysis, it expands in several directions such as Banach spaces, fixed point theory, nonsmooth analysis, minimax theory, variational calculus and inequalities, critical point theory, monotone, maximal monotone and pseudomonotone operators, and evolution problems.

Pattern Recognition

Christian Bauckhage,Juergen Gall,Alexander Schwing
Pattern Recognition Book PDF

Author : Christian Bauckhage,Juergen Gall,Alexander Schwing
Publisher : Springer Nature
Page : 734 pages
File Size : 51,6 Mb
Release : 2022-01-13
Category : Computers
ISBN : 9783030926595

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Pattern Recognition by Christian Bauckhage,Juergen Gall,Alexander Schwing Pdf

This book constitutes the refereed proceedings of the 43rd DAGM German Conference on Pattern Recognition, DAGM GCPR 2021, which was held during September 28 – October 1, 2021. The conference was planned to take place in Bonn, Germany, but changed to a virtual event due to the COVID-19 pandemic. The 46 papers presented in this volume were carefully reviewed and selected from 116 submissions. They were organized in topical sections as follows: machine learning and optimization; actions, events, and segmentation; generative models and multimodal data; labeling and self-supervised learning; applications; and 3D modelling and reconstruction.

Variational and Non-variational Methods in Nonlinear Analysis and Boundary Value Problems

Dumitru Motreanu,Vicentiu D. Radulescu
Variational and Non variational Methods in Nonlinear Analysis and Boundary Value Problems Book PDF

Author : Dumitru Motreanu,Vicentiu D. Radulescu
Publisher : Springer Science & Business Media
Page : 384 pages
File Size : 49,5 Mb
Release : 2013-06-29
Category : Mathematics
ISBN : 9781475769210

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Variational and Non-variational Methods in Nonlinear Analysis and Boundary Value Problems by Dumitru Motreanu,Vicentiu D. Radulescu Pdf

This book reflects a significant part of authors' research activity dur ing the last ten years. The present monograph is constructed on the results obtained by the authors through their direct cooperation or due to the authors separately or in cooperation with other mathematicians. All these results fit in a unitary scheme giving the structure of this work. The book is mainly addressed to researchers and scholars in Pure and Applied Mathematics, Mechanics, Physics and Engineering. We are greatly indebted to Viorica Venera Motreanu for the careful reading of the manuscript and helpful comments on important issues. We are also grateful to our Editors of Kluwer Academic Publishers for their professional assistance. Our deepest thanks go to our numerous scientific collaborators and friends, whose work was so important for us. D. Motreanu and V. Radulescu IX Introduction The present monograph is based on original results obtained by the authors in the last decade. This book provides a comprehensive expo sition of some modern topics in nonlinear analysis with applications to the study of several classes of boundary value problems. Our framework includes multivalued elliptic problems with discontinuities, variational inequalities, hemivariational inequalities and evolution problems. The treatment relies on variational methods, monotonicity principles, topo logical arguments and optimization techniques. Excepting Sections 1 and 3 in Chapter 1 and Sections 1 and 3 in Chapter 2, the material is new in comparison with any other book, representing research topics where the authors contributed. The outline of our work is the following.

Variational Methods in Nonlinear Analysis

Antonio Ambrosetti,K. C. Chang
Variational Methods in Nonlinear Analysis Book PDF

Author : Antonio Ambrosetti,K. C. Chang
Publisher : CRC Press
Page : 300 pages
File Size : 50,7 Mb
Release : 1995
Category : Mathematics
ISBN : 288124937X

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Variational Methods in Nonlinear Analysis by Antonio Ambrosetti,K. C. Chang Pdf

Very Good,No Highlights or Markup,all pages are intact.

Variational Methods

Michael Struwe
Variational Methods Book PDF

Author : Michael Struwe
Publisher : Springer Science & Business Media
Page : 300 pages
File Size : 44,5 Mb
Release : 2000
Category : Mathematics
ISBN : 3540664793

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Variational Methods by Michael Struwe Pdf

Hilbert's talk at the second International Congress of 1900 in Paris marked the beginning of a new era in the calculus of variations. A development began which, within a few decades, brought tremendous success, highlighted by the 1929 theorem of Ljusternik and Schnirelman on the existence of three distinct prime closed geodesics on any compact surface of genus zero, and the 1930/31 solution of Plateau's problem by Douglas and Rad??. The book gives a concise introduction to variational methods and presents an overview of areas of current research in the field. The third edition gives a survey on new developments in the field. References have been updated and a small number of mistakes have been rectified.

Progress in Variational Methods

Chungen Liu,Yiming Long
Progress in Variational Methods Book PDF

Author : Chungen Liu,Yiming Long
Publisher : World Scientific
Page : 249 pages
File Size : 49,8 Mb
Release : 2010
Category : Mathematics
ISBN : 9789814327848

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Progress in Variational Methods by Chungen Liu,Yiming Long Pdf

In the last forty years, nonlinear analysis has been broadly and rapidly developed. Lectures presented in the International Conference on Variational Methods at the Chern Institute of Mathematics in Tianjin of May 2009 reflect this development from different angles. This volume contains articles based on lectures in the following areas of nonlinear analysis: critical point theory, Hamiltonian dynamics, partial differential equations and systems, KAM theory, bifurcation theory, symplectic geometry, geometrical analysis, and celestial mechanics. Combinations of topological, analytical (especially variational), geometrical, and algebraic methods in these researches play important roles. In this proceedings, introductory materials on new theories and surveys on traditional topics are also given. Further perspectives and open problems on hopeful research topics in related areas are described and proposed. Researchers, graduate and postgraduate students from a wide range of areas in mathematics and physics will find contents in this proceedings are helpful.

Visualization Handbook

Charles D. Hansen,Chris R. Johnson
Visualization Handbook Book PDF

Author : Charles D. Hansen,Chris R. Johnson
Publisher : Elsevier
Page : 984 pages
File Size : 43,7 Mb
Release : 2011-08-30
Category : Technology & Engineering
ISBN : 9780080481647

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Visualization Handbook by Charles D. Hansen,Chris R. Johnson Pdf

The Visualization Handbook provides an overview of the field of visualization by presenting the basic concepts, providing a snapshot of current visualization software systems, and examining research topics that are advancing the field. This text is intended for a broad audience, including not only the visualization expert seeking advanced methods to solve a particular problem, but also the novice looking for general background information on visualization topics. The largest collection of state-of-the-art visualization research yet gathered in a single volume, this book includes articles by a “who’s who of international scientific visualization researchers covering every aspect of the discipline, including: · Virtual environments for visualization · Basic visualization algorithms · Large-scale data visualization · Scalar data isosurface methods · Visualization software and frameworks · Scalar data volume rendering · Perceptual issues in visualization · Various application topics, including information visualization. * Edited by two of the best known people in the world on the subject; chapter authors are authoritative experts in their own fields; * Covers a wide range of topics, in 47 chapters, representing the state-of-the-art of scientific visualization.

Geometric Properties for Incomplete Data

Reinhard Klette,Ryszard Kozera,Lyle Noakes,Joachim Weickert
Geometric Properties for Incomplete Data Book PDF

Author : Reinhard Klette,Ryszard Kozera,Lyle Noakes,Joachim Weickert
Publisher : Springer Science & Business Media
Page : 392 pages
File Size : 42,6 Mb
Release : 2006-03-14
Category : Computers
ISBN : 9781402038587

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Geometric Properties for Incomplete Data by Reinhard Klette,Ryszard Kozera,Lyle Noakes,Joachim Weickert Pdf

Computer vision and image analysis require interdisciplinary collaboration between mathematics and engineering. This book addresses the area of high-accuracy measurements of length, curvature, motion parameters and other geometrical quantities from acquired image data. It is a common problem that these measurements are incomplete or noisy, such that considerable efforts are necessary to regularise the data, to fill in missing information, and to judge the accuracy and reliability of these results. This monograph brings together contributions from researchers in computer vision, engineering and mathematics who are working in this area. The book can be read both by specialists and graduate students in computer science, electrical engineering or mathematics who take an interest in data evaluations by approximation or interpolation, in particular data obtained in an image analysis context.