Download or read book Computer Vision ECCV 2022 written by Shai Avidan and published by Springer Nature. This book was released on 2022-10-20 with total page 806 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.

Download or read book Computer Vision ECCV 2020 written by Andrea Vedaldi and published by Springer Nature. This book was released on 2020-10-06 with total page 843 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.

Download or read book A Stochastic Grammar of Images written by Song-Chun Zhu and published by Now Publishers Inc. This book was released on 2007 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Stochastic Grammar of Images is the first book to provide a foundational review and perspective of grammatical approaches to computer vision. In its quest for a stochastic and context sensitive grammar of images, it is intended to serve as a unified frame-work of representation, learning, and recognition for a large number of object categories. It starts out by addressing the historic trends in the area and overviewing the main concepts: such as the and-or graph, the parse graph, the dictionary and goes on to learning issues, semantic gaps between symbols and pixels, dataset for learning and algorithms. The proposal grammar presented integrates three prominent representations in the literature: stochastic grammars for composition, Markov (or graphical) models for contexts, and sparse coding with primitives (wavelets). It also combines the structure-based and appearance based methods in the vision literature. At the end of the review, three case studies are presented to illustrate the proposed grammar. A Stochastic Grammar of Images is an important contribution to the literature on structured statistical models in computer vision.

Download or read book Person Re Identification written by Shaogang Gong and published by Springer Science & Business Media. This book was released on 2014-01-03 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book of its kind dedicated to the challenge of person re-identification, this text provides an in-depth, multidisciplinary discussion of recent developments and state-of-the-art methods. Features: introduces examples of robust feature representations, reviews salient feature weighting and selection mechanisms and examines the benefits of semantic attributes; describes how to segregate meaningful body parts from background clutter; examines the use of 3D depth images and contextual constraints derived from the visual appearance of a group; reviews approaches to feature transfer function and distance metric learning and discusses potential solutions to issues of data scalability and identity inference; investigates the limitations of existing benchmark datasets, presents strategies for camera topology inference and describes techniques for improving post-rank search efficiency; explores the design rationale and implementation considerations of building a practical re-identification system.

Download or read book Monte Carlo Methods written by Adrian Barbu and published by Springer Nature. This book was released on 2020-02-24 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book seeks to bridge the gap between statistics and computer science. It provides an overview of Monte Carlo methods, including Sequential Monte Carlo, Markov Chain Monte Carlo, Metropolis-Hastings, Gibbs Sampler, Cluster Sampling, Data Driven MCMC, Stochastic Gradient descent, Langevin Monte Carlo, Hamiltonian Monte Carlo, and energy landscape mapping. Due to its comprehensive nature, the book is suitable for developing and teaching graduate courses on Monte Carlo methods. To facilitate learning, each chapter includes several representative application examples from various fields. The book pursues two main goals: (1) It introduces researchers to applying Monte Carlo methods to broader problems in areas such as Computer Vision, Computer Graphics, Machine Learning, Robotics, Artificial Intelligence, etc.; and (2) it makes it easier for scientists and engineers working in these areas to employ Monte Carlo methods to enhance their research.

Download or read book Deep Learning with Python written by Francois Chollet and published by Simon and Schuster. This book was released on 2017-11-30 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance

Download or read book Forensic Art and Illustration written by Karen T. Taylor and published by CRC Press. This book was released on 2000-09-15 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the number of stranger-on-stranger crimes increases, solving these crimes becomes more challenging. Forensic illustration has become increasingly important as a tool in identifying both perpetrators and victims. Now a leading forensic artist, who has taught this subject at law enforcement academies, schools, and universities internationally, off

Download or read book The Scientific Revolution written by Steven Shapin and published by University of Chicago Press. This book was released on 2018-11-05 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This scholarly and accessible study presents “a provocative new reading” of the late sixteenth- and seventeenth-century advances in scientific inquiry (Kirkus Reviews). In The Scientific Revolution, historian Steven Shapin challenges the very idea that any such a “revolution” ever took place. Rejecting the narrative that a new and unifying paradigm suddenly took hold, he demonstrates how the conduct of science emerged from a wide array of early modern philosophical agendas, political commitments, and religious beliefs. In this analysis, early modern science is shown not as a set of disembodied ideas, but as historically situated ways of knowing and doing. Shapin shows that every principle identified as the modernizing essence of science—whether it’s experimentalism, mathematical methodology, or a mechanical conception of nature—was in fact contested by sixteenth- and seventeenth-century practitioners with equal claims to modernity. Shapin argues that this contested legacy is nevertheless rightly understood as the origin of modern science, its problems as well as its acknowledged achievements. This updated edition includes a new bibliographic essay featuring the latest scholarship. “An excellent book.” —Anthony Gottlieb, New York Times Book Review

Download or read book Simulating Humans written by Norman I. Badler and published by Oxford University Press, USA. This book was released on 1993-09-02 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: The area of simulated human figures is an active research area in computer graphics, and Norman Badler's group at the University of Pennsylvania is one of the leaders in the field. This book summarizes the state of the art in simulating human figures, discusses many of the interesting application areas, and makes some assumptions and predictions about where the field is going.

Download or read book Lectures in Pattern Recognition written by Ulf Grenander and published by . This book was released on 1976 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computer Vision written by Simon J. D. Prince and published by Cambridge University Press. This book was released on 2012-06-18 with total page 599 pages. Available in PDF, EPUB and Kindle. Book excerpt: A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms.

Download or read book From Gestalt Theory to Image Analysis written by Agnès Desolneux and published by Springer Science & Business Media. This book was released on 2007-12-18 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a new theory in Computer Vision yielding elementary techniques to analyze digital images. These techniques are a mathematical formalization of the Gestalt theory. From the mathematical viewpoint the closest field to it is stochastic geometry, involving basic probability and statistics, in the context of image analysis. The book is mathematically self-contained, needing only basic understanding of probability and calculus. The text includes more than 130 illustrations, and numerous examples based on specific images on which the theory is tested. Detailed exercises at the end of each chapter help the reader develop a firm understanding of the concepts imparted.

Download or read book Computer Graphics and Geometric Modelling written by Max K. Agoston and published by Springer Science & Business Media. This book was released on 2005-01-04 with total page 960 pages. Available in PDF, EPUB and Kindle. Book excerpt: Possibly the most comprehensive overview of computer graphics as seen in the context of geometric modeling, this two-volume work covers implementation and theory in a thorough and systematic fashion. It covers the computer graphics part of the field of geometric modeling and includes all the standard computer graphics topics. The CD-ROM features two companion programs.

Download or read book Algorithms written by Sanjoy Dasgupta and published by McGraw-Hill Higher Education. This book was released on 2006 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and easy to digest. Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include:The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated. Carefully chosen advanced topics that can be skipped in a standard one-semester course but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text DasGupta also offers a Solutions Manual which is available on the Online Learning Center."Algorithms is an outstanding undergraduate text equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel it is a joy to read." Tim Roughgarden Stanford University

Download or read book Crowdsourcing in Computer Vision written by Adriana Kovashka and published by . This book was released on 2016-11-30 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of how crowdsourcing has been used in computer vision, enabling a computer vision researcher who has previously not collected non-expert data to devise a data collection strategy. It will also be of help to researchers who focus broadly on crowdsourcing to examine how the latter has been applied in computer vision.

Download or read book Computer Vision written by Linda G. Shapiro and published by Pearson. This book was released on 2001 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: For upper level courses in Computer Vision and Image Analysis.Provides necessary theory and examples for students and practitioners who will work in fields where significant information must be extracted automatically from images. Appropriate for those interested in multimedia, art and design, geographic information systems, and image databases, in addition to the traditional areas of automation, image science, medical imaging, remote sensing and computer cartography. The text provides a basic set of fundamental concepts and algorithms for analyzing images, and discusses some of the exciting evolving application areas of computer vision.

Download or read book Lectures in Pattern Theory written by U. Grenander and published by Springer. This book was released on 1978-02-21 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many persons have helped the author with comments and corrections, and I would like to mention D. E. McClure, I. Frolow, J. Silverstein, D. Town, and especially W. Freiberger for his helpful suggestions and encouragement. The work in Chapters 6 and 7 has been influenced and stimulated by discussions with other members of the Center for Neural Sciences, especially with L. Cooper and H. Kucera. I would like to thank F. John, J. P. LaSalle, L. Sirovich, and G. Whitham for accepting the manuscript for the series Applied Mathematical Sciences published by Springer-Verlag. This research project has been supported by the Division of Mathematical and Computer Sciences of the National Science Foundation and (the work on language abduction, pattern processors, and patterns in program behavior) by the Information Systems Program of the Office of Naval Research. I greatly appreciate the understanding and positive interest shown by John Pasta, Kent Curtiss, Bruce Barnes, Sally Sedelov vi PREFACE and Bob Agins of the Foundation, and by Marvin Denicoff of the Office of Naval Research. I am indebted to Mrs. E. Fonseca for her untiring and careful preparation of the manuscript, to Miss E. Addison for her skillful help with the many diagrams, and to S.V. Spinacci for the final typing. I gratefully acknowledge permission to reproduce figures, as mentioned in the text, from Cambridge University Press and from Hayden Book Company. Also, to Professor J. Carbury for permission to use his illustration on page 704.