Computer Vision and Machine Intelligence in Medical Image Analysis, Mousumi Gupta; Debanjan Konar; Siddhartha Bhattach
Автор: Siddhartha Bhattacharyya; Debanjan Konar; Jan Plat Название: Hybrid Machine Intelligence for Medical Image Analysis ISBN: 9811389292 ISBN-13(EAN): 9789811389290 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered include automated region of interest detection of magnetic resonance images based on center of gravity; brain tumor detection through low-level features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer-aided detection of mammographic lesions using convolutional neural networks.
Автор: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 60190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Автор: Om Prakash Verma; Sudipta Roy; Subhash Chandra Pan Название: Advancement of Machine Intelligence in Interactive Medical Image Analysis ISBN: 9811510997 ISBN-13(EAN): 9789811510991 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book discusses major technical advances and research findings in the field of machine intelligence in medical image analysis. This book provides insights into the basic science involved in processing, analysing, and utilising all aspects of advanced computational intelligence in medical decision-making based on medical imaging.
Автор: Michael Bowles Название: Machine Learning in Python: Essential Techniques for Predictive Analysis ISBN: 1119559960 ISBN-13(EAN): 9781119559962 Издательство: Wiley Рейтинг: Цена: 42240.00 T Наличие на складе: Невозможна поставка. Описание: Raised on the south side of Chicago, Jonathan Brooks moved as far away as possible as soon as he could. But through unforeseen events he found himself not only back in Englewood but also serving as a pastor and community leader. In this book he challenges Christians to be fully present in their communities, helping local churches rediscover that loving our neighbors means loving our neighborhoods.
Автор: Baochang Zhang Название: Machine Learning and Visual Perception ISBN: 3110595532 ISBN-13(EAN): 9783110595536 Издательство: Walter de Gruyter Цена: 61920.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Machine Learning and Visual Perception provides an up-to-date overview on the topic, including the PAC model, decision tree, Bayesian learning, support vector machines, AdaBoost, compressive sensing and so on.Both classic and novel algorithms are introduced in classifier design, face recognition, deep learning, time series recognition, image classification, and object detection.
Автор: Xingni Zhou, Zhiyuan Ren, Yanzhuo Ma, Kai Fan, Ji Xiang Название: Data structures based on linear relations ISBN: 3110595575 ISBN-13(EAN): 9783110595574 Издательство: Walter de Gruyter Цена: 80520.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Data structures is a key course for computer science and related majors. This book presents a variety of practical or engineering cases and derives abstract concepts from concrete problems. Besides basic concepts and analysis methods, it introduces basic data types such as sequential list, tree as well as graph. This book can be used as an undergraduate textbook, as a training textbook or a self-study textbook for engineers.
Название: Decision forests for computer vision and medical image analysis ISBN: 1447149289 ISBN-13(EAN): 9781447149286 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This practical, easy-to-follow book reviews the theoretical underpinnings of decision forests, organizing the existing literature in a new, general-purpose forest model. Includes exercises and experiments; slides, videos and more reside at a companion website.
Автор: Antonio Criminisi; J Shotton Название: Decision Forests for Computer Vision and Medical Image Analysis ISBN: 144716962X ISBN-13(EAN): 9781447169628 Издательство: Springer Рейтинг: Цена: 116450.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This practical, easy-to-follow book reviews the theoretical underpinnings of decision forests, organizing the existing literature in a new, general-purpose forest model. Includes exercises and experiments; slides, videos and more reside at a companion website.
Автор: Xingni Zhou, Zhiyuan Ren, Yanzhuo Ma, Kai Fan, Ji Xiang Название: Non-linear Data Structures and Data Processing ISBN: 3110676052 ISBN-13(EAN): 9783110676051 Издательство: Walter de Gruyter Цена: 80520.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
The systematic description starts with basic theory and applications of different kinds of data structures, including storage structures and models. It also explores on data processing methods such as sorting, index and search technologies. Due to its numerous exercises the book is a helpful reference for graduate students, lecturers.
Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images.
Examines the methodology of classification of medical images that covers the taxonomy of both supervised and unsupervised models, algorithms, applications and challenges
Discusses recent advances in Artificial Neural Networks, machine learning, and deep learning in clinical applications
Introduces several techniques for medical image processing and analysis for CAD systems design
Автор: Salman Khan, Hossein Rahmani, Syed Afaq Ali Shah, Mohammed Bennamoun Название: A Guide to Convolutional Neural Networks for Computer Vision ISBN: 1681732785 ISBN-13(EAN): 9781681732787 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 102570.00 T Наличие на складе: Невозможна поставка. Описание: Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision.This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs. The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation.This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.
Автор: Jennifer Boger, Victoria Young, Jesse Hoey, Tizneem Jiancaro, Alex Mihailidis Название: Zero-Effort Technologies: Considerations, Challenges, and Use in Health, Wellness, and Rehabilitation, Second Edition ISBN: 1681732866 ISBN-13(EAN): 9781681732862 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 82230.00 T Наличие на складе: Невозможна поставка. Описание: This book introduces zero-effort technologies (ZETs), an emerging class of technologies that require little or no effort from the people who use them. ZETs use advanced computing techniques, such as computer vision, sensor fusion, decision-making and planning, machine learning, and the Internet of Things to autonomously perform the collection, analysis, and application of data about the user and/or his/her context. This book begins with an overview of ZETs, then presents concepts related to their development, including pervasive intelligent technologies and environments, design principles, and considerations regarding use. The book discusses select examples of the latest in ZET development before concluding with thoughts regarding future directions of the field.
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