Overview
Part of the book series: Mathematics and Visualization (MATHVISUAL)
Included in the following conference series:
Conference proceedings info: IVLOPDE 2016.
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About this book
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.
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Table of contents (11 papers)
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Front Matter
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Image Reconstruction from Incomplete Data
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Front Matter
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Image Enhancement, Restoration and Registration
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Front Matter
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3D Image Understanding and Classification
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Front Matter
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Machine Learning and Big Data Analysis
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Front Matter
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Back Matter
Other volumes
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Imaging, Vision and Learning Based on Optimization and PDEs
Editors and Affiliations
Bibliographic Information
Book Title: Imaging, Vision and Learning Based on Optimization and PDEs
Book Subtitle: IVLOPDE, Bergen, Norway, August 29 – September 2, 2016
Editors: Xue-Cheng Tai, Egil Bae, Marius Lysaker
Series Title: Mathematics and Visualization
DOI: https://doi.org/10.1007/978-3-319-91274-5
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-91273-8Published: 20 November 2018
eBook ISBN: 978-3-319-91274-5Published: 19 November 2018
Series ISSN: 1612-3786
Series E-ISSN: 2197-666X
Edition Number: 1
Number of Pages: VIII, 255
Number of Illustrations: 28 b/w illustrations, 67 illustrations in colour
Topics: Image Processing and Computer Vision, Pattern Recognition, Computational Mathematics and Numerical Analysis, Optimization, Partial Differential Equations, Computer Graphics