Brain And Nature Inspired Learning Computation And Recognition
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| Author | : Licheng Jiao |
| Publisher | : Elsevier |
| Total Pages | : 790 |
| Release | : 2020-01-18 |
| Genre | : Technology & Engineering |
| ISBN | : 0128204044 |
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
| Author | : Shai Avidan |
| Publisher | : Springer Nature |
| Total Pages | : 810 |
| Release | : 2022-10-22 |
| Genre | : Computers |
| ISBN | : 3031198212 |
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
| Author | : Sagit Valeev |
| Publisher | : Elsevier |
| Total Pages | : 314 |
| Release | : 2021-02-18 |
| Genre | : Technology & Engineering |
| ISBN | : 0128220678 |
Process Safety and Big Data discusses the principles of process safety and advanced information technologies. It explains how these principles are applied to the process industry and provides examples of applications in process safety control and decision support systems.This book helps to address problems that researchers face in industry that are the result of increased process complexity and that have an impact on safety issues. It shows ways to tackle these safety issues by implementing modern information technologies, such as big data analysis and artificial intelligence. It provides an integrated approach to modern information technologies used in control and management of process safety in industry. The book also considers indicators and criteria in effective safety decisions, and addresses the issue of how big data would provide support for improved, autonomous, data-driven decisions. - Paves the way for the digital transformation of safety science and safety management - Takes a system approach to advanced information technologies used in process safety - Applies big data technologies to process safety - Includes multiple pertinent case studies
| Author | : Licheng Jiao |
| Publisher | : Elsevier |
| Total Pages | : 788 |
| Release | : 2020-01-31 |
| Genre | : Technology & Engineering |
| ISBN | : 9780128197950 |
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
| Author | : Akitoshi Hanazawa |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 176 |
| Release | : 2010-09-22 |
| Genre | : Mathematics |
| ISBN | : 3642040241 |
"Brain-inspired information technology" is one of key concepts for the development of information technology in the next generation. Explosive progress of computer technology has been continuing based on a simple principle called "if-then rule". This means that the programmer of software have to direct every action of the computer programs in response to various inputs. There inherently is a limitation of complexity because we human have a limited capacity for managing complex systems. Actually, many bugs, mistakes of programming, exist in computer software, and it is quite difficult to extinguish them. The parts of computer programs where computer viruses attack are also a kind of programming mistakes, called security hole. Of course, human body or nervous system is not perfect. No creator or director, however, exists for us. The function of our brain is equipped by learning, self-organization, natural selection, and etc, resulting in adaptive and flexible information system. Brain-inspired information technology is aiming to realize such nature-made information processing system by using present computer system or specific hardware. To do so, researchers in various research fields are getting together to inspire each other and challenge cooperatively for the same goal.
| Author | : Management Association, Information Resources |
| Publisher | : IGI Global |
| Total Pages | : 1810 |
| Release | : 2016-07-26 |
| Genre | : Computers |
| ISBN | : 1522507892 |
As technology continues to become more sophisticated, mimicking natural processes and phenomena also becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for man-made computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications takes an interdisciplinary approach to the topic of natural computing, including emerging technologies being developed for the purpose of simulating natural phenomena, applications across industries, and the future outlook of biologically and nature-inspired technologies. Emphasizing critical research in a comprehensive multi-volume set, this publication is designed for use by IT professionals, researchers, and graduate students studying intelligent computing.
| Author | : Robert Kozma |
| Publisher | : Academic Press |
| Total Pages | : 398 |
| Release | : 2023-10-11 |
| Genre | : Computers |
| ISBN | : 0323958168 |
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
| Author | : Jagjit Singh Dhatterwal |
| Publisher | : CRC Press |
| Total Pages | : 341 |
| Release | : 2024-07-24 |
| Genre | : Technology & Engineering |
| ISBN | : 104008818X |
This book introduces the theories and methods of Nature-Inspired Robotics in artificial intelligence. Software and hardware technologies, alongside theories and methods, illustrate the application of bio-inspired artificial intelligence. It includes discussions on topics such as Robot Control Manipulators, Geometric Transformation, Robotic Drive Systems and Nature Inspired Robotic Neural System. Elaborating upon recent progress made in five distinct configurations of nature-inspired computing, it explores the potential applications of this technology in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. · Discusses advances in cutting-edge technology in brain-inspired computing, perception technologies and aspects of neuromorphic electronics · Offers a thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms · Provides comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviours · Includes cognitive behaviour of Inspired Robotics and cognitive technologies with applications in Artificial Intelligence · Contains practical discussions of neuromorphic devices based on chalcogenide and organic materials. This text acts as a reference book for students, scholars, and industry professionals.
| Author | : Hongjiang Song |
| Publisher | : Lulu.com |
| Total Pages | : 382 |
| Release | : 2018-05-30 |
| Genre | : Technology & Engineering |
| ISBN | : 1387847163 |
Nature-inspired VLSI circuit technology offers unique approach for studying, analyzing, designing, and implementing VLSI circuits through perception, reasoning and action mimicking the nature. Such circuit technology covers various aspects of nature-inspired VLSI circuit design techniques, such as the design rule bases, design principles, computing and information processing algorithms, sensing and interfacing techniques, energy harvesting and power management.
| Author | : Hossam Haick |
| Publisher | : Elsevier |
| Total Pages | : 1191 |
| Release | : 2024-10-24 |
| Genre | : Science |
| ISBN | : 0443156859 |
Nature-Inspired Sensors presents and discusses the basic principles and latest developments in nature-inspired sensing and biosensing materials, along with the design and mechanisms for analyzing their potential in multifunctional sensing applications. Sections provide a comprehensive review of certain fundamental mechanisms in different living creatures including humans, animals, and plants. In addition, the book presents and discusses ways for imitating various nature-inspired structural features and their functional properties such as hierarchical, interlocked, porous, bristle-like structures, and hetero-layered brick-and-mortar structures. Sections also highlight the utility of these structures and their properties for sensing functions, which include static coloration, self-cleaning, adhesive, underwater navigation and object detection, electric charge generation, and sensitive olfactory functions for detecting various substances. This is followed by an appraisal of accumulating knowledge and its translation from the laboratory to the point-of-care phase, using selective sensors as well as desktop and wearable artificial sensing devices, e.g., electronic noses and electronic skins, in conjunction with AI-assisted data processing and decision-making in the targeted field of application. - Discusses current strategies for fabricating nature-derived bio/chemical sensors - Presents ways to apply nature-derived bio/chemical sensors in real life - Discusses the future of nature derived bio/chemical sensors
