Data Science and Visual Computing
Data Science and Visual Computing

Author: Rae Earnshaw

Publisher: Springer Nature

Published: 2019-08-30

Total Pages: 108

ISBN-13: 3030243672

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Data science addresses the need to extract knowledge and information from data volumes, often from real-time sources in a wide variety of disciplines such as astronomy, bioinformatics, engineering, science, medicine, social science, business, and the humanities. The range and volume of data sources has increased enormously over time, particularly those generating real-time data. This has posed additional challenges for data management and data analysis of the data and effective representation and display. A wide range of application areas are able to benefit from the latest visual tools and facilities. Rapid analysis is needed in areas where immediate decisions need to be made. Such areas include weather forecasting, the stock exchange, and security threats. In areas where the volume of data being produced far exceeds the current capacity to analyze all of it, attention is being focussed how best to address these challenges. Optimum ways of addressing large data sets across a variety of disciplines have led to the formation of national and institutional Data Science Institutes and Centers. Being driven by national priority, they are able to attract support for research and development within their organizations and institutions to bring together interdisciplinary expertise to address a wide variety of problems. Visual computing is a set of tools and methodologies that utilize 2D and 3D images to extract information from data. Such methods include data analysis, simulation, and interactive exploration. These are analyzed and discussed.

Introduction to Visual Computing
Introduction to Visual Computing

Author: Aditi Majumder

Publisher: CRC Press

Published: 2018-01-31

Total Pages: 376

ISBN-13: 1482244926

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Introduction to Visual Computing: Core Concepts in Computer Vision, Graphics, and Image Processing covers the fundamental concepts of visual computing. Whereas past books have treated these concepts within the context of specific fields such as computer graphics, computer vision or image processing, this book offers a unified view of these core concepts, thereby providing a unified treatment of computational and mathematical methods for creating, capturing, analyzing and manipulating visual data (e.g. 2D images, 3D models). Fundamentals covered in the book include convolution, Fourier transform, filters, geometric transformations, epipolar geometry, 3D reconstruction, color and the image synthesis pipeline. The book is organized in four parts. The first part provides an exposure to different kinds of visual data (e.g. 2D images, videos and 3D geometry) and the core mathematical techniques that are required for their processing (e.g. interpolation and linear regression.) The second part of the book on Image Based Visual Computing deals with several fundamental techniques to process 2D images (e.g. convolution, spectral analysis and feature detection) and corresponds to the low level retinal image processing that happens in the eye in the human visual system pathway. The next part of the book on Geometric Visual Computing deals with the fundamental techniques used to combine the geometric information from multiple eyes creating a 3D interpretation of the object and world around us (e.g. transformations, projective and epipolar geometry, and 3D reconstruction). This corresponds to the higher level processing that happens in the brain combining information from both the eyes thereby helping us to navigate through the 3D world around us. The last two parts of the book cover Radiometric Visual Computing and Visual Content Synthesis. These parts focus on the fundamental techniques for processing information arising from the interaction of light with objects around us, as well as the fundamentals of creating virtual computer generated worlds that mimic all the processing presented in the prior sections. The book is written for a 16 week long semester course and can be used for both undergraduate and graduate teaching, as well as a reference for professionals.

Image Statistics in Visual Computing
Image Statistics in Visual Computing

Author: Tania Pouli

Publisher: CRC Press

Published: 2013-12-13

Total Pages: 360

ISBN-13: 1439874905

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To achieve the complex task of interpreting what we see, our brains rely on statistical regularities and patterns in visual data. Knowledge of these regularities can also be considerably useful in visual computing disciplines, such as computer vision, computer graphics, and image processing. The field of natural image statistics studies the regular

Visual Computing
Visual Computing

Author: Markus Groß

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 345

ISBN-13: 3642850235

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Advances in computing and communications have brought about an increasing demand for visual information. Visual Computing addresses the principles behind "visual technology", and provides readers with a good understanding of how the integration of Computer Graphics, Visual Perception and Imaging is achieved. Included in the book is an overview of important research areas within this integration which will be useful for further work in the field. Foundations of visual perception and psychophysics are presented as well as basic methods of imaging and computer vision. This book serves as an excellent reference and textbook for those who wish to apply or study "visual computing technology."

Deep Learning in Visual Computing
Deep Learning in Visual Computing

Author: Hassan Ugail

Publisher: CRC Press

Published: 2022-07-07

Total Pages: 140

ISBN-13: 1000625427

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Deep learning is an artificially intelligent entity that teaches itself and can be utilized to make predictions. Deep learning mimics the human brain and provides learned solutions addressing many challenging problems in the area of visual computing. From object recognition to image classification for diagnostics, deep learning has shown the power of artificial deep neural networks in solving real world visual computing problems with super-human accuracy. The introduction of deep learning into the field of visual computing has meant to be the death of most of the traditional image processing and computer vision techniques. Today, deep learning is considered to be the most powerful, accurate, efficient and effective method with the potential to solve many of the most challenging problems in visual computing. This book provides an insight into deep machine learning and the challenges in visual computing to tackle the novel method of machine learning. It introduces readers to the world of deep neural network architectures with easy-to-understand explanations. From face recognition to image classification for diagnosis of cancer, the book provides unique examples of solved problems in applied visual computing using deep learning. Interested and enthusiastic readers of modern machine learning methods will find this book easy to follow. They will find it a handy guide for designing and implementing their own projects in the field of visual computing.

Visual Computing
Visual Computing

Author: Richard Mark Friedhoff

Publisher: Times Books

Published: 2000

Total Pages: 141

ISBN-13: 9780716750598

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"Illustrated with classical works of art, images from vision science, and computer generated tableaux, Visual Computing is a celebration of an amazing new field."--BOOK JACKET.

Big Data and Visual Analytics
Big Data and Visual Analytics

Author: Sang C. Suh

Publisher: Springer

Published: 2018-01-15

Total Pages: 262

ISBN-13: 331963917X

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This book provides users with cutting edge methods and technologies in the area of big data and visual analytics, as well as an insight to the big data and data analytics research conducted by world-renowned researchers in this field. The authors present comprehensive educational resources on big data and visual analytics covering state-of-the art techniques on data analytics, data and information visualization, and visual analytics. Each chapter covers specific topics related to big data and data analytics as virtual data machine, security of big data, big data applications, high performance computing cluster, and big data implementation techniques. Every chapter includes a description of an unique contribution to the area of big data and visual analytics. This book is a valuable resource for researchers and professionals working in the area of big data, data analytics, and information visualization. Advanced-level students studying computer science will also find this book helpful as a secondary textbook or reference.

Visual Computing for Medicine
Visual Computing for Medicine

Author: Bernhard Preim

Publisher: Newnes

Published: 2013-11-07

Total Pages: 1017

ISBN-13: 0124159796

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Visual Computing for Medicine, Second Edition, offers cutting-edge visualization techniques and their applications in medical diagnosis, education, and treatment. The book includes algorithms, applications, and ideas on achieving reliability of results and clinical evaluation of the techniques covered. Preim and Botha illustrate visualization techniques from research, but also cover the information required to solve practical clinical problems. They base the book on several years of combined teaching and research experience. This new edition includes six new chapters on treatment planning, guidance and training; an updated appendix on software support for visual computing for medicine; and a new global structure that better classifies and explains the major lines of work in the field. Complete guide to visual computing in medicine, fully revamped and updated with new developments in the field Illustrated in full color Includes a companion website offering additional content for professors, source code, algorithms, tutorials, videos, exercises, lessons, and more

Visual Computing for Cultural Heritage
Visual Computing for Cultural Heritage

Author: Fotis Liarokapis

Publisher: Springer Nature

Published: 2020-04-07

Total Pages: 444

ISBN-13: 3030371913

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This book provides insights into the state of the art of digital cultural heritage using computer graphics, image processing, computer vision, visualization and reconstruction, virtual and augmented reality and serious games. It aims at covering the emergent approaches for digitization and preservation of Cultural Heritage, both in its tangible and intangible facets. Advancements in Digital Cultural Heritage research have been abundant in recent years covering a wide assortment of topics, ranging from visual data acquisition, pre-processing, classification, analysis and synthesis, 3D modelling and reconstruction, semantics and symbolic representation, metadata description, repository and archiving, to new forms of interactive and personalized presentation, visualization and immersive experience provision via advanced computer graphics, interactive virtual and augmented environments, serious games and digital storytelling. Different aspects pertaining to visual computing with regard to tangible (books, images, paintings, manuscripts, uniforms, maps, artefacts, archaeological sites, monuments) and intangible (e.g. dance and performing arts, folklore, theatrical performances) cultural heritage preservation, documentation, protection and promotion are covered, including rendering and procedural modelling of cultural heritage assets, keyword spotting in old documents, drone mapping and airborne photogrammetry, underwater recording and reconstruction, gamification, visitor engagement, animated storytelling, analysis of choreographic patterns, and many more. The book brings together and targets researchers from the domains of computing, engineering, archaeology and the arts, and aims at underscoring the potential for cross-fertilization and collaboration among these communities.

Visual Computing
Visual Computing

Author: Tosiyasu L. Kunii

Publisher: Springer Science & Business Media

Published: 2013-04-17

Total Pages: 926

ISBN-13: 443168204X

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This volume presents the proceedings of the 10th International Conference of the Computer Graphics Society, CG International '92, Visual Computing - Integrating Computer Graphics with Computer Vision -, held at Kogakuin University, Tokyo in Japan from June 22-26,1992. Since its foundation in 1983, this conference has continued to attract high quality research articles in all aspects of computer graphics and its applications. Previous conferences in this series were held in Japan (1983-1987), in Switzerland (1988), in the United Kingdom (1989), in Singapore (1990), and in the United States of America (1991). Future CG International conferences are planned in Switzerland (1993), in Australia (1994), and in the United Kingdom (1995). It has been the editor's dream to research the integration of computer graphics with computer vision through data structures. The conference the editor put together in Los Angeles in 1975 involving the UCLA and IEEE Computer Societies had to spell out these three areas explicitly in the conference title, "computer graphics," "pattern recognition" and "data structures," as well as in the title of the proceedings published by IEEE Computer Society Press. In 1985, the editor gave the name "visual computer" to machines having all the three functionalities as seen in the journal under that name from Springer. Finally, the research in integrating visual information processing has now reached reality as seen in this proceedings of CG International '92. Chapters on virtual reality, and on tools and environments provide examples.