Imaging Vision And Learning Based On Optimization And Pdes
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Imaging Vision And Learning Based On Optimization And Pdes
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Author : Xue-Cheng Tai
language : en
Publisher: Springer
Release Date : 2018-11-19
Imaging Vision And Learning Based On Optimization And Pdes written by Xue-Cheng Tai and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-19 with Computers categories.
This volume presents the peer-reviewed proceedings of the international conference Imaging, Vision and Learning Based on Optimization and PDEs (IVLOPDE), held in Bergen, Norway, in August/September 2016. The contributions cover state-of-the-art research on mathematical techniques for image processing, computer vision and machine learning based on optimization and partial differential equations (PDEs). It has become an established paradigm to formulate problems within image processing and computer vision as PDEs, variational problems or finite dimensional optimization problems. This compact yet expressive framework makes it possible to incorporate a range of desired properties of the solutions and to design algorithms based on well-founded mathematical theory. A growing body of research has also approached more general problems within data analysis and machine learning from the same perspective, and demonstrated the advantages over earlier, more established algorithms. This volume will appeal to all mathematicians and computer scientists interested in novel techniques and analytical results for optimization, variational models and PDEs, together with experimental results on applications ranging from early image formation to high-level image and data analysis.
Proceedings Of The International Congress Of Mathematicians 2018 Icm 2018 In 4 Volumes
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Author : Boyan Sirakov
language : en
Publisher: World Scientific
Release Date : 2019-02-27
Proceedings Of The International Congress Of Mathematicians 2018 Icm 2018 In 4 Volumes written by Boyan Sirakov and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-27 with Mathematics categories.
The Proceedings of the ICM publishes the talks, by invited speakers, at the conference organized by the International Mathematical Union every 4 years. It covers several areas of Mathematics and it includes the Fields Medal and Nevanlinna, Gauss and Leelavati Prizes and the Chern Medal laudatios.
Handbook Of Variational Methods For Nonlinear Geometric Data
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Author : Philipp Grohs
language : en
Publisher: Springer Nature
Release Date : 2020-04-03
Handbook Of Variational Methods For Nonlinear Geometric Data written by Philipp Grohs and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-03 with Mathematics categories.
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.
Interactive Data Processing And 3d Visualization Of The Solid Earth
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Author : Daniel Patel
language : en
Publisher: Springer Nature
Release Date : 2022-02-21
Interactive Data Processing And 3d Visualization Of The Solid Earth written by Daniel Patel and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-21 with Computers categories.
This book presents works detailing the application of processing and visualization techniques for analyzing the Earth’s subsurface. The topic of the book is interactive data processing and interactive 3D visualization techniques used on subsurface data. Interactive processing of data together with interactive visualization is a powerful combination which has in the recent years become possible due to hardware and algorithm advances in. The combination enables the user to perform interactive exploration and filtering of datasets while simultaneously visualizing the results so that insights can be made immediately. This makes it possible to quickly form hypotheses and draw conclusions. Case studies from the geosciences are not as often presented in the scientific visualization and computer graphics community as e.g., studies on medical, biological or chemical data. This book will give researchers in the field of visualization and computer graphics valuable insight into the open visualization challenges in the geosciences, and how certain problems are currently solved using domain specific processing and visualization techniques. Conversely, readers from the geosciences will gain valuable insight into relevant visualization and interactive processing techniques. Subsurface data has interesting characteristics such as its solid nature, large range of scales and high degree of uncertainty, which makes it challenging to visualize with standard methods. It is also noteworthy that parallel fields of research have taken place in geosciences and in computer graphics, with different terminology when it comes to representing geometry, describing terrains, interpolating data and (example-based) synthesis of data. The domains covered in this book are geology, digital terrains, seismic data, reservoir visualization and CO2 storage. The technologies covered are 3D visualization, visualization of large datasets, 3D modelling, machine learning, virtual reality, seismic interpretation and multidisciplinary collaboration. People within any of these domains and technologies are potential readers of the book.
Handbook Of Medical Image Computing And Computer Assisted Intervention
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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2019-10-18
Handbook Of Medical Image Computing And Computer Assisted Intervention written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-18 with Computers categories.
Handbook of Medical Image Computing and Computer Assisted Intervention presents important advanced methods and state-of-the art research in medical image computing and computer assisted intervention, providing a comprehensive reference on current technical approaches and solutions, while also offering proven algorithms for a variety of essential medical imaging applications. This book is written primarily for university researchers, graduate students and professional practitioners (assuming an elementary level of linear algebra, probability and statistics, and signal processing) working on medical image computing and computer assisted intervention. - Presents the key research challenges in medical image computing and computer-assisted intervention - Written by leading authorities of the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society - Contains state-of-the-art technical approaches to key challenges - Demonstrates proven algorithms for a whole range of essential medical imaging applications - Includes source codes for use in a plug-and-play manner - Embraces future directions in the fields of medical image computing and computer-assisted intervention
Digital Image Processing Analysis And Computer Vision Using Nonlinear Partial Differential Equations
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Author : Tudor Barbu
language : en
Publisher: Springer Nature
Release Date : 2025-05-10
Digital Image Processing Analysis And Computer Vision Using Nonlinear Partial Differential Equations written by Tudor Barbu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-10 with Technology & Engineering categories.
This book provides an overview of the applications of partial differential equations (PDEs) to image processing, analysis, and computer vision domains, focusing mainly on the most important contributions of the author in these closely related fields. It addresses almost all the PDE-based image processing and analysis areas, and the connections between partial differential equations, computer vision, and artificial intelligence: PDE-based image filtering, inpainting, compression, segmentation, content-based recognition, indexing and retrieval, and video object detection and tracking, energy-based (variational) and nonlinear diffusion-based models of second and fourth order, nonlinear PDE-based scale-spaces in combination to convolutional neural networks and high-level descriptors to perform edge and feature extraction.
Handbook Of Mathematical Models And Algorithms In Computer Vision And Imaging
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Author : Ke Chen
language : en
Publisher: Springer Nature
Release Date : 2023-02-24
Handbook Of Mathematical Models And Algorithms In Computer Vision And Imaging written by Ke Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-24 with Mathematics categories.
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.
Variational Methods
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Author : Maïtine Bergounioux
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2017-01-11
Variational Methods written by Maïtine Bergounioux and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-11 with Mathematics categories.
With a focus on the interplay between mathematics and applications of imaging, the first part covers topics from optimization, inverse problems and shape spaces to computer vision and computational anatomy. The second part is geared towards geometric control and related topics, including Riemannian geometry, celestial mechanics and quantum control. Contents: Part I Second-order decomposition model for image processing: numerical experimentation Optimizing spatial and tonal data for PDE-based inpainting Image registration using phase・amplitude separation Rotation invariance in exemplar-based image inpainting Convective regularization for optical flow A variational method for quantitative photoacoustic tomography with piecewise constant coefficients On optical flow models for variational motion estimation Bilevel approaches for learning of variational imaging models Part II Non-degenerate forms of the generalized Euler・Lagrange condition for state-constrained optimal control problems The Purcell three-link swimmer: some geometric and numerical aspects related to periodic optimal controls Controllability of Keplerian motion with low-thrust control systems Higher variational equation techniques for the integrability of homogeneous potentials Introduction to KAM theory with a view to celestial mechanics Invariants of contact sub-pseudo-Riemannian structures and Einstein・Weyl geometry Time-optimal control for a perturbed Brockett integrator Twist maps and Arnold diffusion for diffeomorphisms A Hamiltonian approach to sufficiency in optimal control with minimal regularity conditions: Part I Index
Processing Analyzing And Learning Of Images Shapes And Forms Part 2
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Author :
language : en
Publisher: North Holland
Release Date : 2019-10-15
Processing Analyzing And Learning Of Images Shapes And Forms Part 2 written by and has been published by North Holland this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-15 with Mathematics categories.
Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2, Volume 20, surveys the contemporary developments relating to the analysis and learning of images, shapes and forms, covering mathematical models and quick computational techniques. Chapter cover Alternating Diffusion: A Geometric Approach for Sensor Fusion, Generating Structured TV-based Priors and Associated Primal-dual Methods, Graph-based Optimization Approaches for Machine Learning, Uncertainty Quantification and Networks, Extrinsic Shape Analysis from Boundary Representations, Efficient Numerical Methods for Gradient Flows and Phase-field Models, Recent Advances in Denoising of Manifold-Valued Images, Optimal Registration of Images, Surfaces and Shapes, and much more.
Level Set And Pde Based Reconstruction Methods In Imaging
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Author : Martin Burger
language : en
Publisher: Springer
Release Date : 2013-10-17
Level Set And Pde Based Reconstruction Methods In Imaging written by Martin Burger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-17 with Mathematics categories.
This book takes readers on a tour through modern methods in image analysis and reconstruction based on level set and PDE techniques, the major focus being on morphological and geometric structures in images. The aspects covered include edge-sharpening image reconstruction and denoising, segmentation and shape analysis in images, and image matching. For each, the lecture notes provide insights into the basic analysis of modern variational and PDE-based techniques, as well as computational aspects and applications.