Автор: Danica Kragic; Ville Kyrki Название: Unifying Perspectives in Computational and Robot Vision ISBN: 1441945350 ISBN-13(EAN): 9781441945358 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Assembled in this volume is a collection of some of the state-of-the-art methods that are using computer vision and machine learning techniques as applied in robotic applications. Currently there is a gap between research conducted in the computer vision and robotics communities.
Автор: A. Pugh Название: Robot Vision ISBN: 3662097737 ISBN-13(EAN): 9783662097731 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Over the past five years robot vision has emerged as a subject area with its own identity. Users and researchers entering the field of robot vision for the first time will encounter a bewildering array of publications on all aspects of computer vision of which robot vision forms a part.
Автор: Yu Sun; Aman Behal; Chi-Kit Ronald Chung Название: New Development in Robot Vision ISBN: 3662438585 ISBN-13(EAN): 9783662438589 Издательство: Springer Рейтинг: Цена: 16979.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Intensity-Difference Based Monocular Visual Odometry for Planetary Rovers.- Incremental Light Bundle Adjustment: Probabilistic Analysis and Application to Robotic Navigation.- Online Learning of Vision-Based Robot Control during Autonomous Operation.- Semantic and Spatial Content Fusion for Scene Recognition.- Modeling paired objects and their interaction.- Multi-modal Manhattan World Structure Estimation for Domestic Robots.- Improving RGB-D Scene Reconstruction Using Rolling Shutter Rectification.- RMSD: A 3D Real-time Mid-Level Scene Description System.- Probabilistic Active Recognition of Multiple Objects using Hough-based Geometric Matching Features.
Описание: The book includes topics, such as: path planning, avoiding obstacles, following the path, go-to-goal control, localization, and visual-based motion control. Four different control algorithms, Type-1 fuzzy logic, Type-2 Fuzzy Logic, Decision Tree Control, and Gaussian Control have been used in overall system design.
Автор: Hartley, Zisserman Название: Multiple View Geometry in Computer Vision ISBN: 0521540518 ISBN-13(EAN): 9780521540513 Издательство: Cambridge Academ Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The theory and practice of scene reconstruction are described in detail in a unified framework. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition.
Автор: Prince Название: Computer Vision ISBN: 1107011795 ISBN-13(EAN): 9781107011793 Издательство: Cambridge Academ Рейтинг: Цена: 11563.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: With minimal prerequisites, the book starts from the basics of probability and model fitting and works up to real examples that the reader can implement and modify to build useful vision systems. Primarily meant for advanced undergraduate and graduate students, the detailed methodological presentation will also be useful for practitioners of computer vision.
Автор: Marco, Leo Название: Computer Vision for Assistive Healthcare ISBN: 0128134453 ISBN-13(EAN): 9780128134450 Издательство: Elsevier Science Рейтинг: Цена: 14317.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Computer Vision for Assistive Healthcare describes how advanced computer vision techniques provide tools to support common human needs such as mental functioning, personal mobility, sensory functions and daily living activities. It describes how computer vision techniques - such as image processing, pattern recognition, machine learning and Language Processing and Computer Graphics- can cooperate with Robotics to provide such tools. The range of application areas covered are:
Mental functioning
Personal mobility
Sensory functions
Daily living activities
The reader will learn:
What are the emerging computer vision techniques for supporting mental functioning and to develop a Socially Assistive Robot (SAR)
The algorithms for analysing human behaviour beginning with visual data derived from environmental and wearable sensors ('first person vision')
How smart interfaces and virtual reality tools lead to the development of advanced rehabilitation systems able to perform human action and activity recognition using vision based techniques allowing a natural interaction experience
How Robotics Agent Coachers that can assist people with movement disorders during the execution of motor exercises
The technology behind intelligent wheelchairs
How computer vision technologies have the potential to assist blind people to independently access, understand, and explore the environments (both indoor and outdoor)
Computer vision-based solutions recently employed for safety and health monitoring: Fall detection, life log, and vital parameter monitoring
The first book to give the state-of-the-art computer vision techniques and tools for assistive healthcare
Broad range of topic areas ranging from Image processing, pattern recognition, machine learning to robotics, natural language processing and computer graphics
Wide range of application areas ranging from mobility, sensory substitution, safety and security, to mental and physical rehabilitation and training
Written by leading researchers in this growing field of research
Contains pieces of code
Describes the outstanding research challenges still to be tackled, giving researchers good indicators of research opportunities
Автор: Chen, Mei Название: Computer Vision for Microscopy Image Analysis ISBN: 0128149728 ISBN-13(EAN): 9780128149720 Издательство: Elsevier Science Рейтинг: Цена: 17854.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
High-throughput microscopy enables researchers to acquire thousands of images automatically over a short time, making it possible to conduct large-scale, image-based experiments for biological or biomedical discovery. However, visual analysis of large-scale image data is a daunting task. The post-acquisition component of high-throughput microscopy experiments calls for effective and efficient computer vision techniques.
Computer Vision for Microscopy Image Analysis provides a comprehensive and in-depth introduction to state-of-the-art computer vision techniques for microscopy image analysis, demonstrating how they can be effectively applied to biological and medical data.
The reader of the book will learn:
How computer vision analysis can automate and enhance human assessment of microscopy images for discovery
The important steps in microscopy image analysis
State-of-the-art methods for microscopy image analysis including machine learning and deep neural network approaches
This reference on the state-of-the-art computer vision methods in microscopy image analysis is suitable for researchers and graduate students interested in analyzing microscopy images or for developing toolsets for general biomedical image analysis applications.
Each topic contains a comprehensive overview of the field, followed by in-depth presentation of a state-of-the-art approach
Perspectives and content contributed by both technologists and biologists
Tackles specific problems of detection, segmentation, classification, tracking, cellular event detection
Contains the fundamentals of object measurement in microscopy images
Contains open source data and toolsets for microscopy image analysis on an accompanying website
Автор: Millan Escriva Название: Building Computer Vision Projects with OpenCV 4 and C++ ISBN: 1838644679 ISBN-13(EAN): 9781838644673 Издательство: Неизвестно Рейтинг: Цена: 9194.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. By taking this Learning Path, you will be able to work on complex projects that involves image processing, motion detection, and image segmentation.
Автор: Sunila Gollapudi Название: Learn Computer Vision Using OpenCV ISBN: 1484242602 ISBN-13(EAN): 9781484242605 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples. The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python.
The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you'll work with object detection, video storage and interpretation, and human detection using OpenCV.
Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision.
After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work. What You Will LearnUnderstand what computer vision is, and its overall application in intelligent automation systemsDiscover the deep learning techniques required to build computer vision applicationsBuild complex computer vision applications using the latest techniques in OpenCV, Python, and NumPyCreate practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysisWho This Book Is ForThose who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications.
Автор: Bertalmio, Marcelo (associate Professor, Informati Название: Vision models for high dynamic range and wide colour gamut imaging ISBN: 0128138947 ISBN-13(EAN): 9780128138946 Издательство: Elsevier Science Рейтинг: Цена: 19370.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
To enhance the overall viewing experience (for cinema, TV, games, AR/VR) the media industry is continuously striving to improve image quality. Currently the emphasis is on High Dynamic Range (HDR) and Wide Colour Gamut (WCG) technologies, which yield images with greater contrast and more vivid colours. The uptake of these technologies, however, has been hampered by the significant challenge of understanding the science behind visual perception. Vision Models for High Dynamic Range and Wide Colour Gamut Imaging provides university researchers and graduate students in computer science, computer engineering, vision science, as well as industry R&D engineers, an insight into the science and methods for HDR and WCG. It presents the underlying principles and latest practical methods in a detailed and accessible way, highlighting how the use of vision models is a key element of all state-of-the-art methods for these emerging technologies.
Presents the underlying vision science principles and models that are essential to the emerging technologies of HDR and WCG.
Explores state-of-the-art techniques for tone and gamut mapping.
Discusses open challenges and future directions of HDR and WCG research.
Автор: Diego Alexander et al Название: Pattern Recognition Applications in Engineering ISBN: 179981839X ISBN-13(EAN): 9781799818397 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 28967.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The implementation of data and information analysis has become a trending solution within multiple professions. New tools and approaches are continually being developed within data analysis to further solve the challenges that come with professional strategy. Pattern recognition is an innovative method that provides comparison techniques and defines new characteristics within the information acquisition process. Despite its recent trend, a considerable amount of research regarding pattern recognition and its various strategies is lacking.
Pattern Recognition Applications in Engineering is an essential reference source that discusses various strategies of pattern recognition algorithms within industrial and research applications and provides examples of results in different professional areas including electronics, computation, and health monitoring. Featuring research on topics such as condition monitoring, data normalization, and bio-inspired developments, this book is ideally designed for analysts; researchers; civil, mechanical, and electronic engineers; computing scientists; chemists; academicians; and students.
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