Advancements in Computer Vision and Image Processing, Jose Garcia-Rodriguez
Автор: Snehasis Mukherjee; Suvadip Mukherjee; Dipti Prasa Название: Computer Vision, Graphics, and Image Processing ISBN: 3319681230 ISBN-13(EAN): 9783319681238 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The papers presented are extended versions of the papers of three of the four workshops: Computer Vision Applications, Document Analysis and Recognition and Medical Image Processing. The Computer Vision Application track received 52 submissions and after a rigorous review process, 18 papers were presented.
Автор: Parker J J Название: Algorithms for Image Processing and Computer Vision ISBN: 0470643854 ISBN-13(EAN): 9780470643853 Издательство: Wiley Рейтинг: Цена: 12514.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Programmers, scientists, and engineers are always in need of newer techniques and algorithms to manipulate and interpret images. Algorithms for Image Processing and Computer Vision is an accessible collection of algorithms for common image processing applications that simplifies complicated mathematical calculations.
Автор: V. Temlyakov Название: Multivariate Approximation ISBN: 1108428754 ISBN-13(EAN): 9781108428750 Издательство: Cambridge Academ Рейтинг: Цена: 15365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Starting from classical linear approximation, this is a self-contained presentation of modern multivariate approximation theory that explores its connections with other areas of mathematics. The prerequisites are no more than standard undergraduate mathematics, so the book will be accessible to graduate students and non-specialists.
Описание: Whether an old photograph or a single video frame, there is a wealth of data hidden in a picture. Image processing and pattern analysis play a vital role in engineering science and can be applied in diverse areas to solve existing and practical problems.The Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing discusses the advances of image processing and pattern analysis and addresses how new innovations will cater to the demands of daily life. This handbook provides the resources necessary for technology developers, scientists, and policymakers to adopt and implement new inventions across the globe.The chapters presented in this publication encompass various aspects of recent image processing and pattern analysis innovations including, but not limited to, mobile image tracking, motion picture analysis, pattern classification, multisensory data fusion, 3D imaging, supporting routing protocols, brain computer interfaces, image restoration, and medical imaging.
Автор: Bhuyan, Manas Kamal (department Of Electronics And Electrical Engineering, Indian Institute Of Technology Guwahati, India) Название: Computer vision and image processing ISBN: 0367265737 ISBN-13(EAN): 9780367265731 Издательство: Taylor&Francis Рейтинг: Цена: 49764.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The focus of the book is on image acquisition and image formation models, radiometric models of image formation, image formation in the camera, image processing concepts, concept of feature extraction and feature selection for pattern classification/recognition, and advanced concepts.
Автор: Henry Braun, Pavan Turaga, Andreas Spanias, Sameeksha Katoch, Suren Jayasuriya, Cihan Tepedelenlioglu Название: Reconstruction-Free Compressive Vision for Surveillance Applications ISBN: 1681735563 ISBN-13(EAN): 9781681735566 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 10118.00 р. Наличие на складе: Нет в наличии.
Описание: Compressed sensing (CS) allows signals and images to be reliably inferred from undersampled measurements. Exploiting CS allows the creation of new types of high-performance sensors including infrared cameras and magnetic resonance imaging systems. Advances in computer vision and deep learning have enabled new applications of automated systems. In this book, we introduce reconstruction-free compressive vision, where image processing and computer vision algorithms are embedded directly in the compressive domain, without the need for first reconstructing the measurements into images or video. Reconstruction of CS images is computationally expensive and adds to system complexity. Therefore, reconstruction-free compressive vision is an appealing alternative particularly for power-aware systems and bandwidth-limited applications that do not have on-board post-processing computational capabilities. Engineers must balance maintaining algorithm performance while minimizing both the number of measurements needed and the computational requirements of the algorithms. Our study explores the intersection of compressed sensing and computer vision, with the focus on applications in surveillance and autonomous navigation. Other applications are also discussed at the end and a comprehensive list of references including survey papers are given for further reading.
Описание: The book provides insights into the Second International Conference on Computer Vision & Image Processing (CVIP-2017) organized by Department of Computer Science and Engineering of Indian Institute of Technology Roorkee. The topics covered in this book are image/video processing and analysis;
Автор: Henry Braun, Pavan Turaga, Andreas Spanias, Sameeksha Katoch, Suren Jayasuriya, Cihan Tepedelenlioglu Название: Reconstruction-Free Compressive Vision for Surveillance Applications ISBN: 1681735547 ISBN-13(EAN): 9781681735542 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 6930.00 р. Наличие на складе: Нет в наличии.
Описание: Compressed sensing (CS) allows signals and images to be reliably inferred from undersampled measurements. Exploiting CS allows the creation of new types of high-performance sensors including infrared cameras and magnetic resonance imaging systems. Advances in computer vision and deep learning have enabled new applications of automated systems. In this book, we introduce reconstruction-free compressive vision, where image processing and computer vision algorithms are embedded directly in the compressive domain, without the need for first reconstructing the measurements into images or video. Reconstruction of CS images is computationally expensive and adds to system complexity. Therefore, reconstruction-free compressive vision is an appealing alternative particularly for power-aware systems and bandwidth-limited applications that do not have on-board post-processing computational capabilities. Engineers must balance maintaining algorithm performance while minimizing both the number of measurements needed and the computational requirements of the algorithms. Our study explores the intersection of compressed sensing and computer vision, with the focus on applications in surveillance and autonomous navigation. Other applications are also discussed at the end and a comprehensive list of references including survey papers are given for further reading.
Описание: The fields of computer vision and image processing are constantly evolving as new research and applications in these areas emerge. Staying abreast of the most up-to-date developments in this field is necessary in order to promote further research and apply these developments in real-world settings.Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies features timely and informative research on the design and development of computer vision and image processing applications in intelligent agents as well as in multimedia technologies. Covering a diverse set of research in these areas, this publication is ideally designed for use by academicians, technology professionals, students, and researchers interested in uncovering the latest innovations in the field.
Описание: "This book is an essential publication outlining the future research opportunities and emerging technologies in the field of image processing, and the ways multi-core processing can further the field"--
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