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Why Brains Don`t Compute, Purves Dale


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Цена: 74530.00T
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Автор: Purves Dale
Название:  Why Brains Don`t Compute
ISBN: 9783030710668
Издательство: Springer
Классификация:





ISBN-10: 3030710661
Обложка/Формат: Paperback
Страницы: 186
Вес: 0.27 кг.
Дата издания: 08.05.2022
Язык: English
Издание: 1st ed. 2021
Иллюстрации: 47 tables, color; 45 illustrations, color; 9 illustrations, black and white; xv, 168 p. 54 illus., 45 illus. in color.
Размер: 234 x 156 x 10
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book examines what seems to be the basic challenge in neuroscience today: understanding how experience generated by the human brain is related to the physical world we live in.

The Emperor`s New Mind: Concerning Computers, Minds, and the Laws of Physics

Автор: Penrose Roger
Название: The Emperor`s New Mind: Concerning Computers, Minds, and the Laws of Physics
ISBN: 0198784929 ISBN-13(EAN): 9780198784920
Издательство: Oxford Academ
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Цена: 14250.00 T
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Описание: In his bestselling work of popular science, Sir Roger Penrose takes us on a fascinating tour through the basic principles of physics, cosmology, mathematics, and philosophy to show that human thinking can never be emulated by a machine.

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: 136310.00 T
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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.

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: 47130.00 T
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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.

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: 63360.00 T
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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.

Brain-Computer Interfacing

Автор: Rao, Rajesh P. N.
Название: Brain-Computer Interfacing
ISBN: 0521769418 ISBN-13(EAN): 9780521769419
Издательство: Cambridge Academ
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Цена: 82370.00 T
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Описание: This introduction to the field of brain-computer interfacing is designed as a textbook for upper-level undergraduate and first-year graduate courses in neural engineering or brain-computer interfacing for students from a wide range of disciplines. It can also be used as a reference by neuroscientists, computer scientists, engineers, and medical practitioners.

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: 46470.00 T
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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.

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: 99010.00 T
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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.

Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms

Автор: Rina Dechter
Название: Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms
ISBN: 1681734923 ISBN-13(EAN): 9781681734927
Издательство: Mare Nostrum (Eurospan)
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Цена: 93330.00 T
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Описание: Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general. These models are used to perform many reasoning tasks, such as scheduling, planning and learning, diagnosis and prediction, design, hardware and software verification, and bioinformatics. These problems can be stated as the formal tasks of constraint satisfaction and satisfiability, combinatorial optimization, and probabilistic inference. It is well known that the tasks are computationally hard, but research during the past three decades has yielded a variety of principles and techniques that significantly advanced the state of the art. This book provides comprehensive coverage of the primary exact algorithms for reasoning with such models. The main feature exploited by the algorithms is the model's graph. We present inference-based, message-passing schemes (e.g., variable-elimination) and search-based, conditioning schemes (e.g., cycle-cutset conditioning and AND/OR search). Each class possesses distinguished characteristics and in particular has different time vs. space behavior. We emphasize the dependence of both schemes on few graph parameters such as the treewidth, cycle-cutset, and (the pseudo-tree) height. The new edition includes the notion of influence diagrams, which focus on sequential decision making under uncertainty. We believe the principles outlined in the book would serve well in moving forward to approximation and anytime-based schemes. The target audience of this book is researchers and students in the artificial intelligence and machine learning area, and beyond.

Multimodal Learning toward Micro-Video Understanding

Автор: Nie Liqiang, Liu Meng, Song Xuemeng
Название: Multimodal Learning toward Micro-Video Understanding
ISBN: 1681736306 ISBN-13(EAN): 9781681736303
Издательство: Mare Nostrum (Eurospan)
Цена: 103490.00 T
Наличие на складе: Поставка под заказ.
Описание:

Micro-videos, a new form of user-generated content, have been spreading widely across various social platforms, such as Vine, Kuaishou, and TikTok.

Different from traditional long videos, micro-videos are usually recorded by smart mobile devices at any place within a few seconds. Due to their brevity and low bandwidth cost, micro-videos are gaining increasing user enthusiasm. The blossoming of micro-videos opens the door to the possibility of many promising applications, ranging from network content caching to online advertising. Thus, it is highly desirable to develop an effective scheme for high-order micro-video understanding.

Micro-video understanding is, however, non-trivial due to the following challenges: (1) how to represent micro-videos that only convey one or few high-level themes or concepts; (2) how to utilize the hierarchical structure of venue categories to guide micro-video analysis; (3) how to alleviate the influence of low quality caused by complex surrounding environments and camera shake; (4) how to model multimodal sequential data, i.e. textual, acoustic, visual, and social modalities to enhance micro-video understanding; and (5) how to construct large-scale benchmark datasets for analysis. These challenges have been largely unexplored to date.

In this book, we focus on addressing the challenges presented above by proposing some state-of-the-art multimodal learning theories. To demonstrate the effectiveness of these models, we apply them to three practical tasks of micro-video understanding: popularity prediction, venue category estimation, and micro-video routing. Particularly, we first build three large-scale real-world micro-video datasets for these practical tasks. We then present a multimodal transductive learning framework for micro-video popularity prediction. Furthermore, we introduce several multimodal cooperative learning approaches and a multimodal transfer learning scheme for micro-video venue category estimation. Meanwhile, we develop a multimodal sequential learning approach for micro-video recommendation. Finally, we conclude the book and figure out the future research directions in multimodal learning toward micro-video understanding.


Artificial Intelligence: Ethics, Governance and Policy Challenges

Название: Artificial Intelligence: Ethics, Governance and Policy Challenges
ISBN: 9461387164 ISBN-13(EAN): 9789461387165
Издательство: Mare Nostrum (Eurospan)
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Цена: 23100.00 T
Наличие на складе: Невозможна поставка.
Описание: Despite still being in its infancy, artificial intelligence (AI) has already shown enormous potential to advance humanity towards new frontiers of prosperity and growth. Due to its powerful force, however, AI can also pose significant risks, which should be handled with the utmost care, but not with fear. The world's top political leaders have understood AI's disruptive potential and are rushing to secure a competitive advantage in this crucial emerging domain, even at the price of reviving old-fashioned industrial policy. At the same time, academia and civil society are calling for widely shared ethical principles to avoid negative repercussions. In this fast-changing context, Europe is struggling to keep pace with superpowers like the United States and China. This report summarises the work of the CEPS Task Force on Artificial Intelligence, which met throughout 2018. Arguing that the EU and its member states are uniquely positioned to lead the global community towards responsible, sustainable AI development, its members call upon European leaders to focus on leveraging AI's potential to foster sustainable development in line with the 2030 Agenda. The report puts forward 44 recommendations on how to design and promote lawful, responsible and sustainable AI and how to approach future policy and investment decisions with the aim of positioning Europe in the driver's seat to address the most disruptive technology transition of our times.

A Guide to Convolutional Neural Networks for Computer Vision

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)
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Цена: 102570.00 T
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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.

Handbook of Research on Learning in the Age of Transhumanism

Автор: Serap Sisman-Ugur, Gulsun Kurubacak
Название: Handbook of Research on Learning in the Age of Transhumanism
ISBN: 1522584315 ISBN-13(EAN): 9781522584315
Издательство: Mare Nostrum (Eurospan)
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Цена: 204820.00 T
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Описание: As a movement, transhumanism aims to upgrade the human body through science, constantly pushing back the limits of a person by using cutting-edge technologies to fix the human body and upgrade it beyond its natural abilities. Transhumanism can not only change human habits, but it can also change learning practices. By improving human learning, it improves the human organism beyond natural and biological limits. The Handbook of Research on Learning in the Age of Transhumanism is an essential research publication that discusses global values, norms, and ethics that relate to the diverse needs of learners in the digital world and addresses future priorities and needs for transhumanism. The book will identify and scrutinize the needs of learners in the age of transhumanism and examine best practices for transhumanist leaders in learning. Featuring topics such as cybernetics, pedagogy, and sociology, this book is ideal for educators, trainers, instructional designers, curriculum developers, professionals, researchers, academicians, policymakers, and librarians.


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