Information Theory In Computer Vision And Pattern Recognition

Download Information Theory In Computer Vision And Pattern Recognition full books in PDF, epub, and Kindle. Read online Information Theory In Computer Vision And Pattern Recognition ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Information Theory in Computer Vision and Pattern Recognition

Author : Francisco Escolano Ruiz
Publisher : Springer Science & Business Media
ISBN 13 : 1848822979
Total Pages : 375 pages
Book Rating : 4.8/5 (488 download)

DOWNLOAD NOW!

Book Synopsis Information Theory in Computer Vision and Pattern Recognition by : Francisco Escolano Ruiz

Download or read book Information Theory in Computer Vision and Pattern Recognition written by Francisco Escolano Ruiz and published by Springer Science & Business Media. This book was released on 2009-07-14 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Francisco Escolano Ruiz
Publisher : Springer
ISBN 13 : 9781848823044
Total Pages : 364 pages
Book Rating : 4.8/5 (23 download)

DOWNLOAD NOW!

Book Synopsis Information Theory in Computer Vision and Pattern Recognition by : Francisco Escolano Ruiz

Download or read book Information Theory in Computer Vision and Pattern Recognition written by Francisco Escolano Ruiz and published by Springer. This book was released on 2009-08-29 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Tools for Image Processing

Author : Miquel Feixas
Publisher : Springer Nature
ISBN 13 : 3031795555
Total Pages : 148 pages
Book Rating : 4.0/5 (317 download)

DOWNLOAD NOW!

Book Synopsis Information Theory Tools for Image Processing by : Miquel Feixas

Download or read book Information Theory Tools for Image Processing written by Miquel Feixas and published by Springer Nature. This book was released on 2022-06-01 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information Theory (IT) tools, widely used in many scientific fields such as engineering, physics, genetics, neuroscience, and many others, are also useful transversal tools in image processing. In this book, we present the basic concepts of IT and how they have been used in the image processing areas of registration, segmentation, video processing, and computational aesthetics. Some of the approaches presented, such as the application of mutual information to registration, are the state of the art in the field. All techniques presented in this book have been previously published in peer-reviewed conference proceedings or international journals. We have stressed here their common aspects, and presented them in an unified way, so to make clear to the reader which problems IT tools can help to solve, which specific tools to use, and how to apply them. The IT basics are presented so as to be self-contained in the book. The intended audiences are students and practitioners of image processing and related areas such as computer graphics and visualization. In addition, students and practitioners of IT will be interested in knowing about these applications. Table of Contents: Preface / Acknowledgments / Information Theory Basics / Image Registration / Image Segmentation / Video Key Frame Selection / Informational Aesthetics Measures / Bibliography / Authors' Biographies

Information Theory, Inference and Learning Algorithms

Author : David J. C. MacKay
Publisher : Cambridge University Press
ISBN 13 : 9780521642989
Total Pages : 694 pages
Book Rating : 4.6/5 (429 download)

DOWNLOAD NOW!

Book Synopsis Information Theory, Inference and Learning Algorithms by : David J. C. MacKay

Download or read book Information Theory, Inference and Learning Algorithms written by David J. C. MacKay and published by Cambridge University Press. This book was released on 2003-09-25 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

Pattern Recognition, Machine Intelligence and Biometrics

Author : Patrick S. P. Wang
Publisher : Springer Science & Business Media
ISBN 13 : 3642224075
Total Pages : 883 pages
Book Rating : 4.6/5 (422 download)

DOWNLOAD NOW!

Book Synopsis Pattern Recognition, Machine Intelligence and Biometrics by : Patrick S. P. Wang

Download or read book Pattern Recognition, Machine Intelligence and Biometrics written by Patrick S. P. Wang and published by Springer Science & Business Media. This book was released on 2012-02-13 with total page 883 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Pattern Recognition, Machine Intelligence and Biometrics" covers the most recent developments in Pattern Recognition and its applications, using artificial intelligence technologies within an increasingly critical field. It covers topics such as: image analysis and fingerprint recognition; facial expressions and emotions; handwriting and signatures; iris recognition; hand-palm gestures; and multimodal based research. The applications span many fields, from engineering, scientific studies and experiments, to biomedical and diagnostic applications, to personal identification and homeland security. In addition, computer modeling and simulations of human behaviors are addressed in this collection of 31 chapters by top-ranked professionals from all over the world in the field of PR/AI/Biometrics. The book is intended for researchers and graduate students in Computer and Information Science, and in Communication and Control Engineering. Dr. Patrick S. P. Wang is a Professor Emeritus at the College of Computer and Information Science, Northeastern University, USA, Zijiang Chair of ECNU, Shanghai, and NSC Visiting Chair Professor of NTUST, Taipei.

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Author : Ruben Vera-Rodriguez
Publisher : Springer
ISBN 13 : 3030134695
Total Pages : 1001 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications by : Ruben Vera-Rodriguez

Download or read book Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications written by Ruben Vera-Rodriguez and published by Springer. This book was released on 2019-03-02 with total page 1001 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Digital Libraries at the Crossroads of Digital Information for the Future

Author : Adam Jatowt
Publisher : Springer Nature
ISBN 13 : 3030340589
Total Pages : 322 pages
Book Rating : 4.0/5 (33 download)

DOWNLOAD NOW!

Book Synopsis Digital Libraries at the Crossroads of Digital Information for the Future by : Adam Jatowt

Download or read book Digital Libraries at the Crossroads of Digital Information for the Future written by Adam Jatowt and published by Springer Nature. This book was released on 2019-10-29 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 21st International Conference on Asia-Pacific Digital Libraries, ICADL 2019, held in Kuala Lumpur, Malaysia, in November 2019. The 13 full, 13 short, and 5 poster papers presented in this volume were carefully reviewed and selected from 54 submissions. The papers were organized in topical sections named: text classification; altmetrics; scholarly data analysis and recommendation; metadata and entities; digital libraries and digital archives management; multimedia processing; search engines; information extraction; and posters.

Advances in Info-Metrics

Author : Min Chen
Publisher : Oxford University Press
ISBN 13 : 0190636718
Total Pages : 557 pages
Book Rating : 4.1/5 (96 download)

DOWNLOAD NOW!

Book Synopsis Advances in Info-Metrics by : Min Chen

Download or read book Advances in Info-Metrics written by Min Chen and published by Oxford University Press. This book was released on 2020-11-06 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: Info-metrics is a framework for modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is an interdisciplinary framework situated at the intersection of information theory, statistical inference, and decision-making under uncertainty. In Advances in Info-Metrics, Min Chen, J. Michael Dunn, Amos Golan, and Aman Ullah bring together a group of thirty experts to expand the study of info-metrics across the sciences and demonstrate how to solve problems using this interdisciplinary framework. Building on the theoretical underpinnings of info-metrics, the volume sheds new light on statistical inference, information, and general problem solving. The book explores the basis of information-theoretic inference and its mathematical and philosophical foundations. It emphasizes the interrelationship between information and inference and includes explanations of model building, theory creation, estimation, prediction, and decision making. Each of the nineteen chapters provides the necessary tools for using the info-metrics framework to solve a problem. The collection covers recent developments in the field, as well as many new cross-disciplinary case studies and examples. Designed to be accessible for researchers, graduate students, and practitioners across disciplines, this book provides a clear, hands-on experience for readers interested in solving problems when presented with incomplete and imperfect information.

Progress in Pattern Recognition, Image Analysis and Applications

Author : José Francisco Martínez-Trinidad
Publisher : Springer Science & Business Media
ISBN 13 : 3540465561
Total Pages : 1014 pages
Book Rating : 4.5/5 (44 download)

DOWNLOAD NOW!

Book Synopsis Progress in Pattern Recognition, Image Analysis and Applications by : José Francisco Martínez-Trinidad

Download or read book Progress in Pattern Recognition, Image Analysis and Applications written by José Francisco Martínez-Trinidad and published by Springer Science & Business Media. This book was released on 2006-10-12 with total page 1014 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th Iberoamerican Congress on Pattern Recognition, CIARP 2006, held in Cancun, Mexico in November 2006. The 99 revised full papers presented together with three keynote articles were carefully reviewed and selected from 239 submissions. The papers cover ongoing research and mathematical methods.

Computer Vision and Pattern Recognition in Environmental Informatics

Author : Zhou, Jun
Publisher : IGI Global
ISBN 13 : 146669436X
Total Pages : 408 pages
Book Rating : 4.4/5 (666 download)

DOWNLOAD NOW!

Book Synopsis Computer Vision and Pattern Recognition in Environmental Informatics by : Zhou, Jun

Download or read book Computer Vision and Pattern Recognition in Environmental Informatics written by Zhou, Jun and published by IGI Global. This book was released on 2015-10-19 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Vision and Pattern Recognition (CVPR) together play an important role in the processes involved in environmental informatics due to their pervasive, non-destructive, effective, and efficient natures. As a result, CVPR has made significant contributions to the field of environmental informatics by enabling multi-modal data fusion and feature extraction, supporting fast and reliable object detection and classification, and mining the intrinsic relationship between different aspects of environmental data. Computer Vision and Pattern Recognition in Environmental Informatics describes a number of methods and tools for image interpretation and analysis, which enables observation, modelling, and understanding of environmental targets. In addition to case studies on monitoring and modeling plant, soil, insect, and aquatic animals, this publication includes discussions on innovative new ideas related to environmental monitoring, automatic fish segmentation and recognition, real-time motion tracking systems, sparse coding and decision fusion, and cell phone image-based classification and provides useful references for professionals, researchers, engineers, and students with various backgrounds within a multitude of communities.

Pattern Recognition and Computer Vision

Author : Shiqi Yu
Publisher : Springer Nature
ISBN 13 : 3031189108
Total Pages : 737 pages
Book Rating : 4.0/5 (311 download)

DOWNLOAD NOW!

Book Synopsis Pattern Recognition and Computer Vision by : Shiqi Yu

Download or read book Pattern Recognition and Computer Vision written by Shiqi Yu and published by Springer Nature. This book was released on 2022-10-27 with total page 737 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 4-volume set LNCS 13534, 13535, 13536 and 13537 constitutes the refereed proceedings of the 5th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2022, held in Shenzhen, China, in November 2022. The 233 full papers presented were carefully reviewed and selected from 564 submissions. The papers have been organized in the following topical sections: Theories and Feature Extraction; Machine learning, Multimedia and Multimodal; Optimization and Neural Network and Deep Learning; Biomedical Image Processing and Analysis; Pattern Classification and Clustering; 3D Computer Vision and Reconstruction, Robots and Autonomous Driving; Recognition, Remote Sensing; Vision Analysis and Understanding; Image Processing and Low-level Vision; Object Detection, Segmentation and Tracking.

High-Dimensional and Low-Quality Visual Information Processing

Author : Yue Deng
Publisher : Springer
ISBN 13 : 3662445263
Total Pages : 108 pages
Book Rating : 4.6/5 (624 download)

DOWNLOAD NOW!

Book Synopsis High-Dimensional and Low-Quality Visual Information Processing by : Yue Deng

Download or read book High-Dimensional and Low-Quality Visual Information Processing written by Yue Deng and published by Springer. This book was released on 2014-09-04 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Generalized Principal Component Analysis

Author : René Vidal
Publisher : Springer
ISBN 13 : 0387878114
Total Pages : 566 pages
Book Rating : 4.3/5 (878 download)

DOWNLOAD NOW!

Book Synopsis Generalized Principal Component Analysis by : René Vidal

Download or read book Generalized Principal Component Analysis written by René Vidal and published by Springer. This book was released on 2016-04-11 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive introduction to the latest advances in the mathematical theory and computational tools for modeling high-dimensional data drawn from one or multiple low-dimensional subspaces (or manifolds) and potentially corrupted by noise, gross errors, or outliers. This challenging task requires the development of new algebraic, geometric, statistical, and computational methods for efficient and robust estimation and segmentation of one or multiple subspaces. The book also presents interesting real-world applications of these new methods in image processing, image and video segmentation, face recognition and clustering, and hybrid system identification etc. This book is intended to serve as a textbook for graduate students and beginning researchers in data science, machine learning, computer vision, image and signal processing, and systems theory. It contains ample illustrations, examples, and exercises and is made largely self-contained with three Appendices which survey basic concepts and principles from statistics, optimization, and algebraic-geometry used in this book. René Vidal is a Professor of Biomedical Engineering and Director of the Vision Dynamics and Learning Lab at The Johns Hopkins University. Yi Ma is Executive Dean and Professor at the School of Information Science and Technology at ShanghaiTech University. S. Shankar Sastry is Dean of the College of Engineering, Professor of Electrical Engineering and Computer Science and Professor of Bioengineering at the University of California, Berkeley.

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Author : Verónica Vasconcelos
Publisher : Springer Nature
ISBN 13 : 3031492498
Total Pages : 151 pages
Book Rating : 4.0/5 (314 download)

DOWNLOAD NOW!

Book Synopsis Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications by : Verónica Vasconcelos

Download or read book Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications written by Verónica Vasconcelos and published by Springer Nature. This book was released on 2023-12-28 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 2-volume set, LNCS 14469 and 14470, constitutes the proceedings of the 26th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2023, which took place in Coimbra, Portugal, in November 2023. The 61 papers presented were carefully reviewed and selected from 106 submissions. And present research in the fields of pattern recognition, artificial intelligence, and related areas.

Moments and Moment Invariants in Pattern Recognition

Author : Jan Flusser
Publisher : John Wiley & Sons
ISBN 13 : 9780470684764
Total Pages : 312 pages
Book Rating : 4.6/5 (847 download)

DOWNLOAD NOW!

Book Synopsis Moments and Moment Invariants in Pattern Recognition by : Jan Flusser

Download or read book Moments and Moment Invariants in Pattern Recognition written by Jan Flusser and published by John Wiley & Sons. This book was released on 2009-11-04 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Moments as projections of an image’s intensity onto a proper polynomial basis can be applied to many different aspects of image processing. These include invariant pattern recognition, image normalization, image registration, focus/ defocus measurement, and watermarking. This book presents a survey of both recent and traditional image analysis and pattern recognition methods, based on image moments, and offers new concepts of invariants to linear filtering and implicit invariants. In addition to the theory, attention is paid to efficient algorithms for moment computation in a discrete domain, and to computational aspects of orthogonal moments. The authors also illustrate the theory through practical examples, demonstrating moment invariants in real applications across computer vision, remote sensing and medical imaging. Key features: Presents a systematic review of the basic definitions and properties of moments covering geometric moments and complex moments. Considers invariants to traditional transforms – translation, rotation, scaling, and affine transform - from a new point of view, which offers new possibilities of designing optimal sets of invariants. Reviews and extends a recent field of invariants with respect to convolution/blurring. Introduces implicit moment invariants as a tool for recognizing elastically deformed objects. Compares various classes of orthogonal moments (Legendre, Zernike, Fourier-Mellin, Chebyshev, among others) and demonstrates their application to image reconstruction from moments. Offers comprehensive advice on the construction of various invariants illustrated with practical examples. Includes an accompanying website providing efficient numerical algorithms for moment computation and for constructing invariants of various kinds, with about 250 slides suitable for a graduate university course. Moments and Moment Invariants in Pattern Recognition is ideal for researchers and engineers involved in pattern recognition in medical imaging, remote sensing, robotics and computer vision. Post graduate students in image processing and pattern recognition will also find the book of interest.

Energy Minimization Methods in Computer Vision and Pattern Recognition

Author : Xue-Cheng Tai
Publisher : Springer
ISBN 13 : 3319146122
Total Pages : 506 pages
Book Rating : 4.3/5 (191 download)

DOWNLOAD NOW!

Book Synopsis Energy Minimization Methods in Computer Vision and Pattern Recognition by : Xue-Cheng Tai

Download or read book Energy Minimization Methods in Computer Vision and Pattern Recognition written by Xue-Cheng Tai and published by Springer. This book was released on 2015-01-07 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the 10th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2015, held in Hong Kong, China, in January 2015. The 36 revised full papers were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on discrete and continuous optimization; image restoration and inpainting; segmentation; PDE and variational methods; motion, tracking and multiview reconstruction; statistical methods and learning; and medical image analysis.

Energy Minimization Methods in Computer Vision and Pattern Recognition

Author : Anand Rangarajan
Publisher : Springer
ISBN 13 : 3540450637
Total Pages : 534 pages
Book Rating : 4.5/5 (44 download)

DOWNLOAD NOW!

Book Synopsis Energy Minimization Methods in Computer Vision and Pattern Recognition by : Anand Rangarajan

Download or read book Energy Minimization Methods in Computer Vision and Pattern Recognition written by Anand Rangarajan and published by Springer. This book was released on 2003-10-02 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2003, held in Lisbon, Portugal in July 2003.The 33 revised full papers presented were carefully reviewed and selected from 66 submissions. The papers are organized in topical sections on unsupervised learning and matching, probabilistic modeling, segmentation and grouping, shape modeling, restoration and reconstruction, and graphs and graph-based methods.