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Exploring Future Opportunities of Brain-Inspired Artificial Intelligence

Exploring Future Opportunities of Brain-Inspired Artificial Intelligence
Author: Bhatia, Madhulika
Publisher: IGI Global
Total Pages: 244
Release: 2023-03-20
Genre: Computers
ISBN: 1668469820

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Applying mechanisms and principles of human intelligence and converging the brain and artificial intelligence (AI) is currently a research trend. The applications of AI in brain simulation are countless. Brain-inspired intelligent systems will improve next-generation information processing by applying theories, techniques, and applications inspired by the information processing principles from the brain. Exploring Future Opportunities of Brain-Inspired Artificial Intelligence focuses on the convergence of AI with brain-inspired intelligence. It presents research on brain-inspired cognitive machines with vision, audition, language processing, and thinking capabilities. Covering topics such as data analysis tools, knowledge representation, and super-resolution, this premier reference source is an essential resource for engineers, developers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.


Bio-inspired Neurocomputing

Bio-inspired Neurocomputing
Author: Akash Kumar Bhoi
Publisher: Springer Nature
Total Pages: 427
Release: 2020-07-21
Genre: Technology & Engineering
ISBN: 9811554951

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This book covers the latest technological advances in neuro-computational intelligence in biological processes where the primary focus is on biologically inspired neuro-computational techniques. The theoretical and practical aspects of biomedical neural computing, brain-inspired computing, bio-computational models, artificial intelligence (AI) and machine learning (ML) approaches in biomedical data analytics are covered along with their qualitative and quantitative features. The contents cover numerous computational applications, methodologies and emerging challenges in the field of bio-soft computing and bio-signal processing. The authors have taken meticulous care in describing the fundamental concepts, identifying the research gap and highlighting the problems with the strategical computational approaches to address the ongoing challenges in bio-inspired models and algorithms. Given the range of topics covered, this book can be a valuable resource for students, researchers as well as practitioners interested in the rapidly evolving field of neurocomputing and biomedical data analytics.


Brain and Nature-Inspired Learning, Computation and Recognition

Brain and Nature-Inspired Learning, Computation and Recognition
Author: Licheng Jiao
Publisher: Elsevier
Total Pages: 788
Release: 2020-01-18
Genre: Technology & Engineering
ISBN: 0128204044

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Brain and Nature-Inspired Learning, Computation and Recognition presents a systematic analysis of neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature. Sections cover new developments and main applications, algorithms and simulations. Developments in brain and nature-inspired learning have promoted interest in image processing, clustering problems, change detection, control theory and other disciplines. The book discusses the main problems and applications pertaining to bio-inspired computation and recognition, introducing algorithm implementation, model simulation, and practical application of parameter setting. Readers will find solutions to problems in computation and recognition, particularly neural networks, natural computing, machine learning and compressed sensing. This volume offers a comprehensive and well-structured introduction to brain and nature-inspired learning, computation, and recognition. Presents an invaluable systematic introduction to brain and nature-inspired learning, computation and recognition Describes the biological mechanisms, mathematical analyses and scientific principles behind brain and nature-inspired learning, calculation and recognition Systematically analyzes neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature Discusses the theory and application of algorithms and neural networks, natural computing, machine learning and compression perception


Brain-Inspired Cognitive Architectures for Artificial Intelligence: BICA*AI 2020

Brain-Inspired Cognitive Architectures for Artificial Intelligence: BICA*AI 2020
Author: Alexei V. Samsonovich
Publisher: Springer Nature
Total Pages: 613
Release: 2020-12-08
Genre: Technology & Engineering
ISBN: 3030655962

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The book focuses on original approaches intended to support the development of biologically inspired cognitive architectures. It bridges together different disciplines, from classical artificial intelligence to linguistics, from neuro- and social sciences to design and creativity, among others. The chapters, based on contributions presented at the Eleventh Annual Meeting of the BICA Society, held on November 10-14, 2020, in Natal, Brazil, discuss emerging methods, theories and ideas towards the realization of general-purpose humanlike artificial intelligence or fostering a better understanding of the ways the human mind works. All in all, the book provides engineers, mathematicians, psychologists, computer scientists and other experts with a timely snapshot of recent research and a source of inspiration for future developments in the broadly intended areas of artificial intelligence and biological inspiration.


Advances in Brain Inspired Cognitive Systems

Advances in Brain Inspired Cognitive Systems
Author: Jinchang Ren
Publisher: Springer
Total Pages: 870
Release: 2018-10-05
Genre: Computers
ISBN: 3030005631

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This book constitutes the refereed proceedings of the 9th International Conference on Advances in Brain Inspired Cognitive Systems, BICS 2018, held in Xi’an, China, in July 2018. The 83 papers presented in this volume were carefully reviewed and selected from 137 submissions. The papers were organized in topical sections named: neural computation; biologically inspired systems; image recognition: detection, tracking and classification; data analysis and natural language processing; and applications.


Artificial Intelligence in the Age of Neural Networks and Brain Computing

Artificial Intelligence in the Age of Neural Networks and Brain Computing
Author: Robert Kozma
Publisher: Academic Press
Total Pages: 398
Release: 2023-10-27
Genre: Computers
ISBN: 0323958168

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Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present 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 possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. 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 Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks


Emergent Neural Computational Architectures Based on Neuroscience

Emergent Neural Computational Architectures Based on Neuroscience
Author: Stefan Wermter
Publisher: Springer
Total Pages: 587
Release: 2003-05-15
Genre: Computers
ISBN: 3540445978

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It is generally understood that the present approachs to computing do not have the performance, flexibility, and reliability of biological information processing systems. Although there is a comprehensive body of knowledge regarding how information processing occurs in the brain and central nervous system this has had little impact on mainstream computing so far. This book presents a broad spectrum of current research into biologically inspired computational systems and thus contributes towards developing new computational approaches based on neuroscience. The 39 revised full papers by leading researchers were carefully selected and reviewed for inclusion in this anthology. Besides an introductory overview by the volume editors, the book offers topical parts on modular organization and robustness, timing and synchronization, and learning and memory storage.


Human Brain and Artificial Intelligence

Human Brain and Artificial Intelligence
Author: Yueming Wang
Publisher: Springer Nature
Total Pages: 163
Release: 2021-04-07
Genre: Computers
ISBN: 9811612889

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This book constitutes the refereed proceedings of the Second International Workshop on Human Brain and Artificial Intelligence, HBAI 2020, held in conjunction with IJCAI-PRICAI 2020, Kyoto, Japan, in January 2021. Due to the COVID-19 pandemic HBAI 2020 was held in the year 2021 and transferred into virtual format. The 11 full papers presented were carefully reviewed and selected from 12 submissions. The papers present most recent research in the fields of brain-inspired computing, brain-machine interfaces, computational neuroscience, brain-related health, neuroimaging, cognition and behavior, learning, and memory, neuron modulation, and closed-loop brain stimulation.