Автор: Nikola K. Kasabov Название: Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence ISBN: 3662577135 ISBN-13(EAN): 9783662577134 Издательство: Springer Рейтинг: Цена: 260870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author’s contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI). BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosciences.
Автор: Nikola K. Kasabov Название: Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence ISBN: 366258607X ISBN-13(EAN): 9783662586075 Издательство: Springer Рейтинг: Цена: 260870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author’s contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI). BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosciences.
Автор: SHANDILYA, SHANDILYA, DEEP & NAG Название: Handbook of research on soft computing and nature-inspired algorithms ISBN: 1522521283 ISBN-13(EAN): 9781522521280 Издательство: Turpin Рейтинг: Цена: 275970.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.
Автор: Walter J. Scheirer Название: Extreme Value Theory-Based Methods for Visual Recognition ISBN: 1627057005 ISBN-13(EAN): 9781627057004 Издательство: Turpin Рейтинг: Цена: 68930.00 T Наличие на складе: Невозможна поставка. Описание: A common feature of many approaches to modeling sensory statistics is an emphasis on capturing the ""average."" From early representations in the brain, to highly abstracted class categories in machine learning for classification tasks, central-tendency models based on the Gaussian distribution are a seemingly natural and obvious choice for modeling sensory data. However, insights from neuroscience, psychology, and computer vision suggest an alternate strategy: preferentially focusing representational resources on the extremes of the distribution of sensory inputs. The notion of treating extrema near a decision boundary as features is not necessarily new, but a comprehensive statistical theory of recognition based on extrema is only now just emerging in the computer vision literature. This book begins by introducing the statistical Extreme Value Theory (EVT) for visual recognition. In contrast to central-tendency modeling, it is hypothesized that distributions near decision boundaries form a more powerful model for recognition tasks by focusing coding resources on data that are arguably the most diagnostic features. EVT has several important properties: strong statistical grounding, better modeling accuracy near decision boundaries than Gaussian modeling, the ability to model asymmetric decision boundaries, and accurate prediction of the probability of an event beyond our experience. The second part of the book uses the theory to describe a new class of machine learning algorithms for decision making that are a measurable advance beyond the state-of-the-art. This includes methods for post-recognition score analysis, information fusion, multi-attribute spaces, and calibration of supervised machine learning algorithms.
Artificial Intelligence in the Age of Neural Networks and Brain Computing demonstrates that existing disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity and smart autonomous search engines. The book covers the major basic ideas of brain-like computing behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as future alternatives. The success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel and Amazon can be interpreted using this book.
Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN)
Authored by top experts, global field pioneers and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making
Edited by high-level academics and researchers in intelligent systems and neural networks
Автор: Waldron Kenneth J., Tokhi Mohammad O., Virk Gurvin Название: Nature-Inspired Mobile Robotics: Proceedings of the 16th International Conference on Climbing and Walking Robots and the Support Technologies for Mobi ISBN: 9814525529 ISBN-13(EAN): 9789814525527 Издательство: World Scientific Publishing Рейтинг: Цена: 295680.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The proceedings provide state-of-the-art scientific and engineering research findings and developments in the area of mobile robotics and assistive technologies. The proceedings collected together peer reviewed articles presented at the CLAWAR 2013 conference. It contains a strong showing of articles on legged locomotion with numbers of legs from two onwards. There is also a good collection of articles on systems that walls climbing, poles balancing, and other more complex structures following the traditional of CLAWAR themes. In addition, the proceedings also cover the subject of robot-human interaction, which focus on a more “human” way of communicating with humanoid robots. As for human assistive devices, proceedings also cover exoskeletal and prosthetic devices, robots for personal and nursing cares to address the issues of ageing population in our society. Finally, the issue of the deployment of robots in society, it social and ethically consideration are also addressed in the proceedings.
Автор: Bhattacharyya, Siddhartha Название: Quantum Inspired Computational Intelligence ISBN: 0128044098 ISBN-13(EAN): 9780128044094 Издательство: Elsevier Science Рейтинг: Цена: 77470.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Quantum Inspired Computational Intelligence: Research and Applications explores the latest quantum computational intelligence approaches, initiatives, and applications in computing, engineering, science, and business. The book explores this emerging field of research that applies principles of quantum mechanics to develop more efficient and robust intelligent systems. Conventional computational intelligence--or soft computing--is conjoined with quantum computing to achieve this objective. The models covered can be applied to any endeavor which handles complex and meaningful information.
Brings together quantum computing with computational intelligence to achieve enhanced performance and robust solutions
Includes numerous case studies, tools, and technologies to apply the concepts to real world practice
Provides the missing link between the research and practice
Автор: Kulkarni Название: Cohort Intelligence: A Socio-inspired Optimization Method ISBN: 3319442538 ISBN-13(EAN): 9783319442532 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This Volume discusses the underlying principles and analysis of the different concepts associated with an emerging socio-inspired optimization tool referred to as Cohort Intelligence (CI). CI algorithms have been coded in Matlab and are freely available from the link provided inside the book. The book demonstrates the ability of CI methodology for solving combinatorial problems such as Traveling Salesman Problem and Knapsack Problem in addition to real world applications from the healthcare, inventory, supply chain optimization and Cross-Border transportation. The inherent ability of handling constraints based on probability distribution is also revealed and proved using these problems.
Название: Bio-Inspired Computing for Information Retrieval Applications ISBN: 1522523758 ISBN-13(EAN): 9781522523758 Издательство: Turpin Рейтинг: Цена: 202050.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The growing presence of biologically-inspired processing has caused significant changes in data retrieval. With the ubiquity of these technologies, more effective and streamlined data processing techniques are available. Bio-Inspired Computing for Information Retrieval Applications is a key resource on the latest advances and research regarding current techniques that have evolved from biologically-inspired processes and its application to a variety of problems. Highlighting multidisciplinary studies on data processing, swarm-based clustering, and evolutionary computation, this publication is an ideal reference source for researchers, academics, professionals, students, and practitioners.
Автор: Vallverdu Jordi, Mazzara Manuel, Talanov Max Название: Advanced Research on Biologically Inspired Cognitive Architectures ISBN: 1522519475 ISBN-13(EAN): 9781522519478 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 189420.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: There are many different approaches to understanding human consciousness. By conducting research to better understand various biological mechanisms, these can be redefined and utilized for technological purposes.Advanced Research on Biologically Inspired Cognitive Architectures is an essential reference source for the latest scholarly research on the biological elements of human cognition and examines the applications of consciousness within computing environments. Featuring exhaustive coverage on a broad range of innovative topics and perspectives, such as artificial intelligence, bio-robotics, and human-computer interaction, this publication is ideally designed for academics, researchers, professionals, graduate students, and practitioners seeking current research on the exploration of the intricacies of consciousness and different approaches of perception.
Автор: Michael Felsberg Название: Probabilistic and Biologically Inspired Feature Representations ISBN: 1681733668 ISBN-13(EAN): 9781681733661 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 66530.00 T Наличие на складе: Невозможна поставка. Описание: pacote do Courseware consiste em duas publicacoes, VeriSMTM - Foundation Courseware e VeriSM - Foundation Study Guide. Este material de treinamento abrange o plano de estudos para a qualificacao da Fundacao VeriSM . O treinamento pode ser entregue em dois dias. Este material didatico e credenciado para preparar o aluno para a certificacao da VeriSM Foundation. O VeriSM Foundation consiste em duas partes: VeriSM Essentials e VeriSM Plus, cada uma cobrindo um dia de treinamento.Os alunos que ja possuem um certificado de Gerenciamento de Servicos (TI) podem se beneficiar do conhecimento que ja possuem. Eles sao o publico-alvo de apenas um treinamento do VeriSM Plus. Ao serem aprovados no exame VeriSM Plus, recebem o certificado VeriSM Foundation.Provedores de treinamento que desejam oferecer um treinamento de um dia sobre principios de gerenciamento de servicos podem decidir oferecer apenas o treinamento VeriSM Essentials. Os alunos que forem aprovados no exame VeriSM Essentials receberao o certificado VeriSM Essentials. Se eles passarem no exame VeriSM Plus mais tarde, receberao automaticamente o certificado VeriSM Foundation.O "courseware" abrange os seguintes topicos:A organizacao do servico (Essentials)Cultura de servico (Essentials)Pessoas e estrutura organizacional (Essentials)O modelo VeriSM (ambos)Praticas Progressivas (Plus)Tecnologias Inovadoras (Plus)O VeriSM e uma abordagem holistica e orientada aos negocios para o Gerenciamento de Servicos, que ajuda a entender o panorama crescente das melhores praticas e como integra-las para oferecer valor ao consumidor.E uma evolucao no pensamento em Gerenciamento de Servicos e oferece uma abordagem atualizada, incluindo as mais recentes praticas e desenvolvimentos tecnologicos, para ajudar as organizacoes a transformar seus negocios para a nova realidade da era digital.O VeriSM e um gerenciamento orientado a valor, evolutivo, responsivo e integrado.VeriSM e uma marca registrada e propriedade da IFDC, a Fundacao Internacional de Competencias Digitais.
Автор: Michael Felsberg Название: Probabilistic and Biologically Inspired Feature Representations ISBN: 1681730235 ISBN-13(EAN): 9781681730233 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 46200.00 T Наличие на складе: Невозможна поставка. Описание: Under the title Probabilistic and Biologically Inspired Feature Representations, this text collects a substantial amount of work on the topic of channel representations. Channel representations are a biologically motivated, wavelet-like approach to visual feature descriptors: they are local and compact, they form a computational framework, and the represented information can be reconstructed. The first property is shared with many histogram- and signature-based descriptors, the latter property with the related concept of population codes. In their unique combination of properties, channel representations become a visual Swiss army knife—they can be used for image enhancement, visual object tracking, as 2D and 3D descriptors, and for pose estimation. In the chapters of this text, the framework of channel representations will be introduced and its attributes will be elaborated, as well as further insight into its probabilistic modeling and algorithmic implementation will be given. Channel representations are a useful toolbox to represent visual information for machine learning, as they establish a generic way to compute popular descriptors such as HOG, SIFT, and SHOT. Even in an age of deep learning, they provide a good compromise between hand-designed descriptors and a-priori structureless feature spaces as seen in the layers of deep networks.
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