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Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence, Thiruvathukal George K., Lu Yung-Hsiang, Kim Jaeyoun


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Автор: Thiruvathukal George K., Lu Yung-Hsiang, Kim Jaeyoun
Название:  Low-Power Computer Vision: Improve the Efficiency of Artificial Intelligence
ISBN: 9780367744700
Издательство: Taylor&Francis
Классификация:


ISBN-10: 0367744708
Обложка/Формат: Hardcover
Страницы: 416
Вес: 0.78 кг.
Дата издания: 23.02.2022
Серия: Chapman & hall/crc computer vision
Язык: English
Иллюстрации: 58 tables, black and white; 61 line drawings, color; 39 line drawings, black and white; 1 halftones, color; 62 illustrations, color; 39 illustrations, black and white
Размер: 23.39 x 15.60 x 2.39 cm
Читательская аудитория: Postgraduate, research & scholarly
Подзаголовок: Improve the efficiency of artificial intelligence
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание: Energy efficiency is critical for running computer vision on battery-powered systems, such as mobile phones or UAVs (unmanned aerial vehicles, or drones). This book collects the methods that have won the annual IEEE Low-Power Computer Vision Challenges since 2015.


The Art of Feature Engineering: Essentials for Machine Learning

Автор: Pablo Duboue
Название: The Art of Feature Engineering: Essentials for Machine Learning
ISBN: 1108709389 ISBN-13(EAN): 9781108709385
Издательство: Cambridge Academ
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Цена: 6970.00 р.
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Описание: This is a guide for data scientists who want to use feature engineering to improve the performance of their machine learning solutions. The book provides a unified view of the field, beginning with basic concepts and techniques, followed by a cross-domain approach to advanced topics, like texts and images, with hands-on case studies.

Computational Models for Cognitive Vision

Автор: Hiranmay Ghosh
Название: Computational Models for Cognitive Vision
ISBN: 1119527864 ISBN-13(EAN): 9781119527862
Издательство: Wiley
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Цена: 7754.00 р.
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Описание:

Learn how to apply cognitive principles to the problems of computer vision

Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The author's ultimate goal is to provide a framework for creation of a machine vision system with the capability and versatility of the human vision.

Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as "artificial intelligence". The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision.

Other topics covered in the book include:

- knowledge representation techniques

- evolution of cognitive architectures

- deep learning approaches for visual cognition

Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision.

We, the Robots?: Regulating Artificial Intelligence and the Limits of the Law

Автор: Chesterman Simon
Название: We, the Robots?: Regulating Artificial Intelligence and the Limits of the Law
ISBN: 1316517683 ISBN-13(EAN): 9781316517680
Издательство: Cambridge Academ
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Цена: 5702.00 р.
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Описание: Should we regulate artificial intelligence? Can we? From self-driving cars and high-speed trading to algorithmic decision-making, the way we live, work, and play is increasingly dependent on AI systems. This book examines how our laws are dealing with AI, as well as what additional rules and institutions are needed.

Artificial Intelligence in Wireless Robotics

Автор: Kwang-Cheng Chen
Название: Artificial Intelligence in Wireless Robotics
ISBN: 8770221189 ISBN-13(EAN): 9788770221184
Издательство: Taylor&Francis
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Цена: 14851.00 р.
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Описание: Robots, autonomous vehicles, unmanned aerial vehicles, and smart factory, will significantly change human living style in digital society. Artificial Intelligence in Wireless Robotics introduces how wireless communications and networking technology enhances facilitation of artificial intelligence in robotics, which bridges basic multi-disciplinary knowledge among artificial intelligence, wireless communications, computing, and control in robotics. A unique aspect of the book is to introduce applying communication and signal processing techniques to enhance traditional artificial intelligence in robotics and multi-agent systems.

The technical contents of this book include fundamental knowledge in robotics, cyber-physical systems, artificial intelligence, statistical decision and Markov decision process, reinforcement learning, state estimation, localization, computer vision and multi-modal data fusion, robot planning, multi-agent systems, networked multi-agent systems, security and robustness of networked robots, and ultra-reliable and low-latency machine-to-machine networking. Examples and exercises are provided for easy and effective comprehension.

Engineers wishing to extend knowledge in the robotics, AI, and wireless communications, would be benefited from this book. In the meantime, the book is ready as a textbook for senior undergraduate students or first-year graduate students in electrical engineering, computer engineering, computer science, and general engineering students. The readers of this book shall have basic knowledge in undergraduate probability and linear algebra, and basic programming capability, in order to enjoy deep reading.

Challenges and Applications for Implementing Machine Learning in Computer Vision

Автор: Ramgopal Kashyap, A.V. Senthil Kumar
Название: Challenges and Applications for Implementing Machine Learning in Computer Vision
ISBN: 1799801837 ISBN-13(EAN): 9781799801832
Издательство: Mare Nostrum (Eurospan)
Цена: 25978.00 р.
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Описание: Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.

Transforming Healthcare with Big Data and AI

Автор: Alex Lui, Anna Farzinder, Mingboo Gong
Название: Transforming Healthcare with Big Data and AI
ISBN: 1641138971 ISBN-13(EAN): 9781641138970
Издательство: Mare Nostrum (Eurospan)
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Цена: 7069.00 р.
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Описание: Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field.

This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.

Computational Intelligence for Machine Learning and Healthcare Informatics

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: 20446.00 р.
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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.

Epistemic Logic for AI and Computer Science

Автор: J.-J. Ch. Meyer, W. van der Hoek
Название: Epistemic Logic for AI and Computer Science
ISBN: 0521602807 ISBN-13(EAN): 9780521602808
Издательство: Cambridge Academ
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Цена: 9186.00 р.
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Описание: This book, based on courses taught at universities and summer schools, provides a broad introduction to the subject; many exercises are included with their solutions.

Frontiers of Intelligent Control and Information Processing

Автор: Liu Derong, Apippi Cesare, Zhao Dongbin
Название: Frontiers of Intelligent Control and Information Processing
ISBN: 9814616877 ISBN-13(EAN): 9789814616874
Издательство: World Scientific Publishing
Цена: 23760.00 р.
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Описание: The current research and development in intelligent control and information processing have been driven increasingly by advancements made from fields outside the traditional control areas, into new frontiers of intelligent control and information processing so as to deal with ever more complex systems with ever growing size of data and complexity.

Causality, Correlation and Artificial Intelligence for Rational Decision Making

Автор: Marwala Tshilidzi
Название: Causality, Correlation and Artificial Intelligence for Rational Decision Making
ISBN: 9814630861 ISBN-13(EAN): 9789814630863
Издательство: World Scientific Publishing
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Цена: 13939.00 р.
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Описание:

Causality has been a subject of study for a long time. Often causality is confused with correlation. Human intuition has evolved such that it has learned to identify causality through correlation. In this book, four main themes are considered and these are causality, correlation, artificial intelligence and decision making. A correlation machine is defined and built using multi-layer perceptron network, principal component analysis, Gaussian Mixture models, genetic algorithms, expectation maximization technique, simulated annealing and particle swarm optimization. Furthermore, a causal machine is defined and built using multi-layer perceptron, radial basis function, Bayesian statistics and Hybrid Monte Carlo methods. Both these machines are used to build a Granger non-linear causality model. In addition, the Neyman-Rubin, Pearl and Granger causal models are studied and are unified. The automatic relevance determination is also applied to extend Granger causality framework to the non-linear domain. The concept of rational decision making is studied, and the theory of flexibly-bounded rationality is used to extend the theory of bounded rationality within the principle of the indivisibility of rationality. The theory of the marginalization of irrationality for decision making is also introduced to deal with satisficing within irrational conditions. The methods proposed are applied in biomedical engineering, condition monitoring and for modelling interstate conflict.

Artificial Intelligence and Computer Vision

Автор: Huimin Lu; Yujie Li
Название: Artificial Intelligence and Computer Vision
ISBN: 331946244X ISBN-13(EAN): 9783319462448
Издательство: Springer
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Цена: 19564.00 р.
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Описание: This edited book presents essential findings in the research fields of artificial intelligence and computer vision, with a primary focus on new research ideas and results for mathematical problems involved in computer vision systems. The book provides an international forum for researchers to summarize the most recent developments and ideas in the field, with a special emphasis on the technical and observational results obtained in the past few years.

Principles Of Artificial Neural Networks (3Rd Edition)

Автор: Graupe Daniel
Название: Principles Of Artificial Neural Networks (3Rd Edition)
ISBN: 9814522732 ISBN-13(EAN): 9789814522731
Издательство: World Scientific Publishing
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Цена: 19008.00 р.
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Описание: Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond.This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition - all with their respective source codes. These case studies demonstrate to the readers in detail how such case studies are designed and executed and how their specific results are obtained.The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining.


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