Information Theory In Computer Vision And Pattern Recognition
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Information Theory In Computer Vision And Pattern Recognition
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Author : Francisco Escolano Ruiz
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-14
Information Theory In Computer Vision And Pattern Recognition written by Francisco Escolano Ruiz 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 2009-07-14 with Computers categories.
Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier design and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information...), principles (maximum entropy, minimax entropy...) and theories (rate distortion theory, method of types...). This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to a cross-fertilization of both areas.
Information Theory In Computer Vision And Pattern Recognition
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Author : Francisco Escolano Ruiz
language : en
Publisher: Springer
Release Date : 2009-08-29
Information Theory In Computer Vision And Pattern Recognition written by Francisco Escolano Ruiz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-29 with Computers categories.
Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier design and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information...), principles (maximum entropy, minimax entropy...) and theories (rate distortion theory, method of types...). This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to a cross-fertilization of both areas.
Progress In Pattern Recognition Image Analysis Computer Vision And Applications
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Author : Ruben Vera-Rodriguez
language : en
Publisher: Springer
Release Date : 2019-03-02
Progress In Pattern Recognition Image Analysis Computer Vision And Applications written by Ruben Vera-Rodriguez and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-02 with Computers categories.
This book constitutes the refereed post-conference proceedings of the 23rd Iberoamerican Congress on Pattern Recognition, CIARP 2018, held in Madrid, Spain, in November 2018 The 112 papers presented were carefully reviewed and selected from 187 submissions The program was comprised of 6 oral sessions on the following topics: machine learning, computer vision, classification, biometrics and medical applications, and brain signals, and also on: text and character analysis, human interaction, and sentiment analysis
Pattern Recognition
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Author : Zeynep Akata
language : en
Publisher: Springer Nature
Release Date : 2021-03-16
Pattern Recognition written by Zeynep Akata and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-16 with Computers categories.
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.
High Dimensional And Low Quality Visual Information Processing
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Author : Yue Deng
language : en
Publisher: Springer
Release Date : 2014-09-04
High Dimensional And Low Quality Visual Information Processing written by Yue Deng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-04 with Technology & Engineering categories.
This thesis primarily focuses on how to carry out intelligent sensing and understand the high-dimensional and low-quality visual information. After exploring the inherent structures of the visual data, it proposes a number of computational models covering an extensive range of mathematical topics, including compressive sensing, graph theory, probabilistic learning and information theory. These computational models are also applied to address a number of real-world problems including biometric recognition, stereo signal reconstruction, natural scene parsing, and SAR image processing.
Computer Vision And Applications
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Author : Bernd Jahne
language : en
Publisher: Academic Press
Release Date : 2000-04-24
Computer Vision And Applications written by Bernd Jahne and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-04-24 with Computers categories.
CD-ROM contains: Searchable version of text with hyperlinks.
Computer Oriented Approaches To Pattern Recognition
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Author : Meisel
language : en
Publisher: Academic Press
Release Date : 1972-07-31
Computer Oriented Approaches To Pattern Recognition written by Meisel and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1972-07-31 with Computers categories.
Computer-Oriented Approaches to Pattern Recognition
Computer Vision Accv 2016 Workshops
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Author : Chu-Song Chen
language : en
Publisher: Springer
Release Date : 2017-03-14
Computer Vision Accv 2016 Workshops written by Chu-Song Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-14 with Computers categories.
The three-volume set, consisting of LNCS 10116, 10117, and 10118, contains carefully reviewed and selected papers presented at 17 workshops held in conjunction with the 13th Asian Conference on Computer Vision, ACCV 2016, in Taipei, Taiwan in November 2016. The 134 full papers presented were selected from 223 submissions. LNCS 10116 contains the papers selected
Computer Vision Accv 2018
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Author : C.V. Jawahar
language : en
Publisher: Springer
Release Date : 2019-05-25
Computer Vision Accv 2018 written by C.V. Jawahar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-25 with Computers categories.
The six volume set LNCS 11361-11366 constitutes the proceedings of the 14th Asian Conference on Computer Vision, ACCV 2018, held in Perth, Australia, in December 2018. The total of 274 contributions was carefully reviewed and selected from 979 submissions during two rounds of reviewing and improvement. The papers focus on motion and tracking, segmentation and grouping, image-based modeling, dep learning, object recognition object recognition, object detection and categorization, vision and language, video analysis and event recognition, face and gesture analysis, statistical methods and learning, performance evaluation, medical image analysis, document analysis, optimization methods, RGBD and depth camera processing, robotic vision, applications of computer vision.
Face Image Analysis By Unsupervised Learning
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Author : Marian Stewart Bartlett
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Face Image Analysis By Unsupervised Learning written by Marian Stewart Bartlett 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 2012-12-06 with Computers categories.
Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis. It draws upon principles of unsupervised learning and information theory to adapt processing to the immediate task environment. In contrast to more traditional approaches to image analysis in which relevant structure is determined in advance and extracted using hand-engineered techniques, Face Image Analysis by Unsupervised Learning explores methods that have roots in biological vision and/or learn about the image structure directly from the image ensemble. Particular attention is paid to unsupervised learning techniques for encoding the statistical dependencies in the image ensemble. The first part of this volume reviews unsupervised learning, information theory, independent component analysis, and their relation to biological vision. Next, a face image representation using independent component analysis (ICA) is developed, which is an unsupervised learning technique based on optimal information transfer between neurons. The ICA representation is compared to a number of other face representations including eigenfaces and Gabor wavelets on tasks of identity recognition and expression analysis. Finally, methods for learning features that are robust to changes in viewpoint and lighting are presented. These studies provide evidence that encoding input dependencies through unsupervised learning is an effective strategy for face recognition. Face Image Analysis by Unsupervised Learning is suitable as a secondary text for a graduate-level course, and as a reference for researchers and practitioners in industry.