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Author: Wenfeng Wang
Publisher: Springer
ISBN: 9811335494
Category : Technology & Engineering
Languages : en
Pages : 177
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Book Description
This book presents the latest findings in the field of brain-inspired intelligence and visual perception (BIVP), and discusses novel research assumptions, including an introduction to brain science and the brain vision hypotheses. Moreover, it introduces readers to the theory and algorithms of BIVP – such as pheromone accumulation and iteration, neural cognitive computing mechanisms, the integration and scheduling of core modules, and brain-inspired perception, motion and control – in a step-by-step manner. Accordingly, it will appeal to university researchers, R&D engineers, undergraduate and graduate students; to anyone interested in robots, brain cognition or computer vision; and to all those wishing to learn about the core theory, principles, methods, algorithms, and applications of BIVP.
Author: Wenfeng Wang
Publisher: Springer
ISBN: 9811335494
Category : Technology & Engineering
Languages : en
Pages : 177
Get Book Here
Book Description
This book presents the latest findings in the field of brain-inspired intelligence and visual perception (BIVP), and discusses novel research assumptions, including an introduction to brain science and the brain vision hypotheses. Moreover, it introduces readers to the theory and algorithms of BIVP – such as pheromone accumulation and iteration, neural cognitive computing mechanisms, the integration and scheduling of core modules, and brain-inspired perception, motion and control – in a step-by-step manner. Accordingly, it will appeal to university researchers, R&D engineers, undergraduate and graduate students; to anyone interested in robots, brain cognition or computer vision; and to all those wishing to learn about the core theory, principles, methods, algorithms, and applications of BIVP.
Author: Katrin Amunts
Publisher: Springer Nature
ISBN: 3030824276
Category : Computers
Languages : en
Pages : 159
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Book Description
This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.
Author: Bhatia, Madhulika
Publisher: IGI Global
ISBN: 1668469820
Category : Computers
Languages : en
Pages : 244
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Book Description
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.
Author: Nikola K. Kasabov
Publisher: Springer
ISBN: 3662577151
Category : Technology & Engineering
Languages : en
Pages : 742
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Book Description
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.
Author: Georg F. Striedter
Publisher:
ISBN: 0195125681
Category : Medical
Languages : en
Pages : 541
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Book Description
This book encourages readers to view similarities and differences in various species as fundamental to a comprehensive understanding of nervous systems.
Author: Francesco Mele
Publisher: Springer
ISBN: 3540755551
Category : Computers
Languages : en
Pages : 632
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Book Description
This book constitutes the refereed proceedings of the Second International Symposium on Brain, Vision and Artificial Intelligence, BVAI 2007. Coverage includes: basic models in visual sciences, cortical mechanism of vision, color processing in natural vision, action oriented vision, visual recognition and attentive modulation, biometric recognition, image segmentation and recognition, disparity calculation and noise analysis, meaning-interaction-emotion, and robot navigation.
Author: Wenfeng Wang
Publisher: Springer Nature
ISBN: 9813342447
Category : Technology & Engineering
Languages : en
Pages : 154
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Book Description
This book seeks to interpret connections between the machine brain, mind and vision in an alternative way and promote future research into the Interdisciplinary Evolution of Machine Brain (IEMB). It gathers novel research on IEMB, and offers readers a step-by-step introduction to the theory and algorithms involved, including data-driven approaches in machine learning, monitoring and understanding visual environments, using process-based perception to expand insights, mechanical manufacturing for remote sensing, reconciled connections between the machine brain, mind and vision, and the interdisciplinary evolution of machine intelligence. This book is intended for researchers, graduate students and engineers in the fields of robotics, Artificial Intelligence and brain science, as well as anyone who wishes to learn the core theory, principles, methods, algorithms, and applications of IEMB.
Author: Qing Wan
Publisher: John Wiley & Sons
ISBN: 3527349790
Category : Technology & Engineering
Languages : en
Pages : 258
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Book Description
Explore the cutting-edge of neuromorphic technologies with applications in Artificial Intelligence In Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics, a team of expert engineers delivers a comprehensive discussion of all aspects of neuromorphic electronics designed to assist researchers and professionals to understand and apply all manner of brain-inspired computing and perception technologies. The book covers both memristic and neuromorphic devices, including spintronic, multi-terminal, and neuromorphic perceptual applications. Summarizing recent progress made in five distinct configurations of brain-inspired computing, the authors explore this promising technology’s potential applications in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. The book also includes: A thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms Comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviors Practical discussions of neuromorphic devices based on chalcogenide and organic materials In-depth examinations of neuromorphic computing and perceptual systems with emerging devices Perfect for materials scientists, biochemists, and electronics engineers, Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics will also earn a place in the libraries of neurochemists, neurobiologists, and neurophysiologists.
Author: Richard E. Passingham
Publisher: OUP Oxford
ISBN: 0191633097
Category : Medical
Languages : en
Pages : 424
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Book Description
The prefrontal cortex makes up almost a quarter of the human brain, and it expanded dramatically during primate evolution. The Neurobiology of the Prefrontal Cortex presents a new theory about its fundamental function. In this important new book, the authors argue that primate-specific parts of the prefrontal cortex evolved to reduce errors in foraging choices, so that particular ancestors of modern humans could overcome periodic food shortages. These developments laid the foundation for working out problems in our imagination, which resulted in the insights that allow humans to avoid errors entirely, at least at times. In the book, the authors detail which parts of the prefrontal cortex evolved exclusively in primates, how its connections explain why the prefrontal cortex alone can perform its function, and why other parts of the brain cannot do what the prefrontal cortex does. Based on an analysis of its evolutionary history, the book uses evidence from lesion, imaging, and cell-recording experiments to argue that the primate prefrontal cortex generates goals from a current behavioural context and that it can do so on the basis of single events. As a result, the prefrontal cortex uses the attentive control of behaviour to augment an older general-purpose learning system, one that evolved very early in the history of animals. This older system learns slowly and cumulatively over many experiences based on reinforcement. The authors argue that a new learning system evolved in primates at a particular time and place in their history, that it did so to decrease the errors inherent in the older learning system, and that severe volatility of food resources provided the driving force for these developments. Written by two leading brain scientists, The Neurobiology of the Prefrontal Cortex is an important contribution to our understanding of the evolution and functioning of the human brain.
Author: Bao-Liang Lu
Publisher: Springer
ISBN: 3642249558
Category : Computers
Languages : en
Pages : 788
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Book Description
The three volume set LNCS 7062, LNCS 7063, and LNCS 7064 constitutes the proceedings of the 18th International Conference on Neural Information Processing, ICONIP 2011, held in Shanghai, China, in November 2011. The 262 regular session papers presented were carefully reviewed and selected from numerous submissions. The papers of part I are organized in topical sections on perception, emotion and development, bioinformatics, biologically inspired vision and recognition, bio-medical data analysis, brain signal processing, brain-computer interfaces, brain-like systems, brain-realistic models for learning, memory and embodied cognition, Clifford algebraic neural networks, combining multiple learners, computational advances in bioinformatics, and computational-intelligent human computer interaction. The second volume is structured in topical sections on cybersecurity and data mining workshop, data mining and knowledge doscovery, evolutionary design and optimisation, graphical models, human-originated data analysis and implementation, information retrieval, integrating multiple nature-inspired approaches, kernel methods and support vector machines, and learning and memory. The third volume contains all the contributions connected with multi-agent systems, natural language processing and intelligent Web information processing, neural encoding and decoding, neural network models, neuromorphic hardware and implementations, object recognition, visual perception modelling, and advances in computational intelligence methods based pattern recognition.
