Structured Computer Vision

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Structured Computer Vision

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Author : S Tanimoto
language : en
Publisher: Elsevier
Release Date : 2014-08-05

Structured Computer Vision written by S Tanimoto and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-05 with Technology & Engineering categories.

Structured Computer Vision

Structured Learning And Prediction In Computer Vision

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Author : Sebastian Nowozin
language : en
Publisher: Now Publishers Inc
Release Date : 2011

Structured Learning And Prediction In Computer Vision written by Sebastian Nowozin and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.

Structured Learning and Prediction in Computer Vision introduces the reader to the most popular classes of structured models in computer vision.

Zeszyty Naukowe Uniwersytetu Dzkiego

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Author : Stefan Hrabec
language : en
Publisher:
Release Date :

Zeszyty Naukowe Uniwersytetu Dzkiego written by Stefan Hrabec and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.

Deep Structure Singularities And Computer Vision

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Author : Ole Fogh Olsen
language : en
Publisher: Springer
Release Date : 2005-12-04

Deep Structure Singularities And Computer Vision written by Ole Fogh Olsen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-04 with Computers categories.

This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Deep Structure, Singularities, and Computer Vision, DSSCV 2005, held in Maastricht, The Netherlands in June 2005. The 14 revised full papers and 8 revised poster papers presented were carefully reviewed and selected for inclusion in the book. They represent the current state-of-the-art in understanding the relation between structural, topological information represented by singularities and metric information of signals, shapes, images, and colors.

Computer Vision

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Author : Richard Szeliski
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-30

Computer Vision written by Richard Szeliski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-30 with Computers categories.

Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques. Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

Visual Communications And Image Processing

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Author :
language : en
Publisher:
Release Date : 1992

Visual Communications And Image Processing written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Image processing categories.

Proceedings

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Author :
language : en
Publisher:
Release Date : 1995

Proceedings written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.

Proceedings of the January 1995 workshop, containing the keynote session, open forums, and sessions on parallel algorithms, load balancing, modeling, software environments, parallel architectures, linear algebra, and various distributed database systems. Open forums offer papers on topics such as di

Large Scale Structured Models For Computer Vision

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Author : Cǎtǎlin-Dumitru Ionescu
language : en
Publisher:
Release Date : 2017

Large Scale Structured Models For Computer Vision written by Cǎtǎlin-Dumitru Ionescu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.

Theoretical Foundations Of Computer Vision

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Author : Walter Kropatsch
language : en
Publisher: Springer
Release Date : 1996

Theoretical Foundations Of Computer Vision written by Walter Kropatsch and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.

Computer Vision is a rapidly growing field of research investigating computational and algorithmic issues associated with image acquisition, processing, and understanding. It serves tasks like manipulation, recognition, mobility, and communication in diverse application areas such as manufacturing, robotics, medicine, security and virtual reality. This volume contains a selection of papers devoted to theoretical foundations of computer vision covering a broad range of fields, e.g. motion analysis, discrete geometry, computational aspects of vision processes, models, morphology, invariance, image compression, 3D reconstruction of shape. Several issues have been identified to be of essential interest to the community: non-linear operators; the transition between continuous to discrete representations; a new calculus of non-orthogonal partially dependent systems.

Advanced Structured Prediction

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Author : Sebastian Nowozin
language : en
Publisher: MIT Press
Release Date : 2014-12-05

Advanced Structured Prediction written by Sebastian Nowozin and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-05 with Computers categories.

An overview of recent work in the field of structured prediction, the building of predictive machine learning models for interrelated and dependent outputs. The goal of structured prediction is to build machine learning models that predict relational information that itself has structure, such as being composed of multiple interrelated parts. These models, which reflect prior knowledge, task-specific relations, and constraints, are used in fields including computer vision, speech recognition, natural language processing, and computational biology. They can carry out such tasks as predicting a natural language sentence, or segmenting an image into meaningful components. These models are expressive and powerful, but exact computation is often intractable. A broad research effort in recent years has aimed at designing structured prediction models and approximate inference and learning procedures that are computationally efficient. This volume offers an overview of this recent research in order to make the work accessible to a broader research community. The chapters, by leading researchers in the field, cover a range of topics, including research trends, the linear programming relaxation approach, innovations in probabilistic modeling, recent theoretical progress, and resource-aware learning. Contributors Jonas Behr, Yutian Chen, Fernando De La Torre, Justin Domke, Peter V. Gehler, Andrew E. Gelfand, Sébastien Giguère, Amir Globerson, Fred A. Hamprecht, Minh Hoai, Tommi Jaakkola, Jeremy Jancsary, Joseph Keshet, Marius Kloft, Vladimir Kolmogorov, Christoph H. Lampert, François Laviolette, Xinghua Lou, Mario Marchand, André F. T. Martins, Ofer Meshi, Sebastian Nowozin, George Papandreou, Daniel Průša, Gunnar Rätsch, Amélie Rolland, Bogdan Savchynskyy, Stefan Schmidt, Thomas Schoenemann, Gabriele Schweikert, Ben Taskar, Sinisa Todorovic, Max Welling, David Weiss, Thomáš Werner, Alan Yuille, Stanislav Živný