Computational and Machine Learning Tools for Archaeological Site Modeling,
Автор: Mansi, Tommaso Passerini, Tiziano Название: Artificial intelligence for computational modeling of the heart ISBN: 012817594X ISBN-13(EAN): 9780128175941 Издательство: Elsevier Science Рейтинг: Цена: 132500.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient's heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications.
Presents recent advances in computational modeling of heart function and artificial intelligence technologies for subject-specific applications
Discusses AI-based technologies for robust anatomical modeling from medical images, data-driven reduction of multi-scale cardiac models, and estimations of physiological parameters from clinical data
Illustrates the technology through concrete clinical applications and discusses potential impacts and next steps needed for clinical translation
Автор: Castiello Название: Computational and Machine Learning Tools for Archaeological Site Modeling ISBN: 3030885690 ISBN-13(EAN): 9783030885694 Издательство: Springer Рейтинг: Цена: 204970.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book describes a novel machine-learning based approach to answer some traditional archaeological problems, relating to archaeological site detection and site locational preferences. Institutional data collected from six Swiss regions (Zurich, Aargau, Grisons, Vaud, Geneva and Fribourg) have been analyzed with an original conceptual framework based on the Random Forest algorithm. It is shown how the algorithm can assist in the modelling process in connection with heterogeneous, incomplete archaeological datasets and related cultural heritage information. Moreover, an in-depth review of past and more recent works of quantitative methods for archaeological predictive modelling is provided. The book guides the readers to set up their own protocol for: i) dealing with uncertain data, ii) predicting archaeological site location, iii) establishing environmental features importance, iv) and suggest a model validation procedure. It addresses both academics and professionals in archaeology and cultural heritage management, and offers a source of inspiration for future research directions in the field of digital humanities and computational archaeology.
Автор: Marieka Brouwer Burg; Hans Peeters; William A. Lov Название: Uncertainty and Sensitivity Analysis in Archaeological Computational Modeling ISBN: 3319278312 ISBN-13(EAN): 9783319278315 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: As very few such techniques have been problematized in a systematicmanner or published in the archaeological literature, this volume aims toprovide guidance and direction to other modelers in the field by distillingsome basic principles for model testing derived from insight gathered in thecase studies presented.
Автор: Pyzer-Knapp Название: Deep Learning for Physical Scientists: Acceleratin g Research with Machine Learning ISBN: 1119408334 ISBN-13(EAN): 9781119408338 Издательство: Wiley Рейтинг: Цена: 65420.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Discover the power of machine learning in the physical sciences with this one-stop resource from a leading voice in the field Deep Learning for Physical Scientists: Accelerating Research with Machine Learning delivers an insightful analysis of the transformative techniques being used in deep learning within the physical sciences. The book offers readers the ability to understand, select, and apply the best deep learning techniques for their individual research problem and interpret the outcome. Designed to teach researchers to think in useful new ways about how to achieve results in their research, the book provides scientists with new avenues to attack problems and avoid common pitfalls and problems.
Practical case studies and problems are presented, giving readers an opportunity to put what they have learned into practice, with exemplar coding approaches provided to assist the reader. From modelling basics to feed-forward networks, the book offers a broad cross-section of machine learning techniques to improve physical science research. Readers will also enjoy: A thorough introduction to the basic classification and regression with perceptrons An exploration of training algorithms, including back propagation and stochastic gradient descent and the parallelization of training An examination of multi-layer perceptrons for learning from descriptors and de-noising data Discussions of recurrent neural networks for learning from sequences and convolutional neural networks for learning from images A treatment of Bayesian optimization for tuning deep learning architectures Perfect for academic and industrial research professionals in the physical sciences, Deep Learning for Physical Scientists: Accelerating Research with Machine Learning will also earn a place in the libraries of industrial researchers who have access to large amounts of data but have yet to learn the techniques to fully exploit that access.
Perfect for academic and industrial research professionals in the physical sciences, Deep Learning for Physical Scientists: Accelerating Research with Machine Learning will also earn a place in the libraries of industrial researchers who have access to large amounts of data but have yet to learn the techniques to fully exploit that access. This book introduces the reader to the transformative techniques involved in deep learning. A range of methodologies are addressed including:*Basic classification and regression with perceptrons *Training algorithms, such as back propagation and stochastic gradient descent and the parallelization of training*Multi-Layer Perceptrons for learning from descriptors, and de-noising data*Recurrent neural networks for learning from sequences*Convolutional neural networks for learning from images*Bayesian optimization for tuning deep learning architecturesEach of these areas has direct application to physical science research, and by the end of the book, the reader should feel comfortable enough to select the methodology which is best for their situation, and be able to implement and interpret outcome of the deep learning model.
The book is designed to teach researchers to think in new ways, providing them with new avenues to attack problems, and avoid roadblocks within their research. This is achieved through the inclusion of case-study like problems at the end of each chapter, which will give the reader a chance to practice what they have just learnt in a close-to-real-world setting, with example 'solutions' provided through an online resource. Market Description This book introduces the reader to the transformative techniques involved in deep learning.
A range of methodologies are addressed including: * Basic classification and regression with perceptrons* Training algorithms, such as back propagation and stochastic gradient descent and the parallelization of training* Multi-Layer Perceptrons for learning from descriptors, and de-noising data* Recurrent neural networks for learning from sequences* Convolutional neural networks for learning from images* Bayesian optimization for tuning deep learning architectures Each of these areas has direct application to physical science research, and by the end of the book, the reader should feel comfortable enough to select the methodology which is best for their situation, and be able to implement and interpret outcome of the deep learning model. The book is designed to teach researchers to think in new ways, providing them with new avenues to attack problems, and avoid roadblocks within their research. This is achieved through the inclusion of case-study like problems at the end of each chapter, which will give the reader a chance to practice what they have just learnt in a close-to-real-world setting, with example 'solutions' provided through an online resource.
Автор: Rajshree Srivastava, Pradeep Kumar Mallick, Siddha Название: Computational Intelligence for Machine Learning and Healthcare Informatics ISBN: 3110647826 ISBN-13(EAN): 9783110647822 Издательство: Walter de Gruyter Цена: 136310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Автор: Saifullah Khalid Название: Applications of Artificial Intelligence in Electrical Engineering ISBN: 1799827186 ISBN-13(EAN): 9781799827184 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 283010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Artificial intelligence is increasingly finding its way into industrial and manufacturing contexts. The prevalence of AI in industry from stock market trading to manufacturing makes it easy to forget how complex artificial intelligence has become. Engineering provides various current and prospective applications of these new and complex artificial intelligence technologies.
Applications of Artificial Intelligence in Electrical Engineering is a critical research book that examines the advancing developments in artificial intelligence with a focus on theory and research and their implications. Highlighting a wide range of topics such as evolutionary computing, image processing, and swarm intelligence, this book is essential for engineers, manufacturers, technology developers, IT specialists, managers, academicians, researchers, computer scientists, and students.
Автор: Bhattacharyya, Siddhartha Название: Hybrid Computational Intelligent Systems ISBN: 1032393025 ISBN-13(EAN): 9781032393025 Издательство: Taylor&Francis Рейтинг: Цена: 163330.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Mehdi Saqalli; Marc Vander Linden Название: Integrating Qualitative and Social Science Factors in Archaeological Modelling ISBN: 3030127222 ISBN-13(EAN): 9783030127220 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers the methodological, epistemological and practical issues of integrating qualitative and socio-anthropological factors into archaeological modeling.
Автор: Saqalli Mehdi, Vander Linden Marc Название: Integrating Qualitative and Social Science Factors in Archaeological Modelling ISBN: 3030127257 ISBN-13(EAN): 9783030127251 Издательство: Springer Рейтинг: Цена: 65210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers the methodological, epistemological and practical issues of integrating qualitative and socio-anthropological factors into archaeological modeling.
Автор: Aboul Ella Hassanien, Ashraf Darwish Название: Machine Learning and Data Mining in Aerospace Technology ISBN: 3030202119 ISBN-13(EAN): 9783030202118 Издательство: Springer Рейтинг: Цена: 186330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book explores the main concepts, algorithms, and techniques of Machine Learning and data mining for aerospace technology. Satellites are the 'eagle eyes' that allow us to view massive areas of the Earth simultaneously, and can gather more data, more quickly, than tools on the ground. Consequently, the development of intelligent health monitoring systems for artificial satellites - which can determine satellites' current status and predict their failure based on telemetry data - is one of the most important current issues in aerospace engineering.
This book is divided into three parts, the first of which discusses central problems in the health monitoring of artificial satellites, including tensor-based anomaly detection for satellite telemetry data and machine learning in satellite monitoring, as well as the design, implementation, and validation of satellite simulators. The second part addresses telemetry data analytics and mining problems, while the last part focuses on security issues in telemetry data.
Автор: Das, S.K., Das, S.P., Dey, N., Hassanien, A.-E. Название: Machine Learning Algorithms for Industrial Applications ISBN: 3030506401 ISBN-13(EAN): 9783030506407 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics.
Автор: Neeraj Mohan Название: Artificial intelligence, machine learning, and data science technologies : ISBN: 0367720914 ISBN-13(EAN): 9780367720919 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, and how all countries around the world are feeling this impact.
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