Brain and Nature Inspired Learning Computation and Recognition

Brain and Nature Inspired Learning  Computation and Recognition
Author: Licheng Jiao,Ronghua Shang,Fang Liu,Weitong Zhang
Publsiher: Elsevier
Total Pages: 788
Release: 2020-01-18
ISBN 10: 0128204044
ISBN 13: 9780128204047
Language: EN, FR, DE, ES & NL

Brain and Nature Inspired Learning Computation and Recognition Book Review:

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

Nature Inspired Computing Concepts Methodologies Tools and Applications

Nature Inspired Computing  Concepts  Methodologies  Tools  and Applications
Author: Management Association, Information Resources
Publsiher: IGI Global
Total Pages: 1780
Release: 2016-07-26
ISBN 10: 1522507892
ISBN 13: 9781522507895
Language: EN, FR, DE, ES & NL

Nature Inspired Computing Concepts Methodologies Tools and Applications Book Review:

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.

Nature Inspired Computing Design Development and Applications

Nature Inspired Computing Design  Development  and Applications
Author: Nunes de Castro, Leandro
Publsiher: IGI Global
Total Pages: 435
Release: 2012-05-31
ISBN 10: 1466615753
ISBN 13: 9781466615755
Language: EN, FR, DE, ES & NL

Nature Inspired Computing Design Development and Applications Book Review:

The observation of nature has been the inspiration for many materials, laws, and theories, as well as computational methods. Nature-Inspired computing Design, Development, and Applications covers all the main areas of natural computing, from methods to computationally synthesized natural phenomena, to computing paradigms based on natural materials. This volume is comprised of ideas and research from nature to develop computational systems or materials to perform computation. Researchers, academic educators, and professionals will find a comprehensive view of all aspects of natural computing with emphasis on its main branches.

Nature Inspired Computation and Machine Learning

Nature Inspired Computation and Machine Learning
Author: Alexander Gelbukh,Félix Castro Espinoza,Sofía N. Galicia-Haro
Publsiher: Springer
Total Pages: 522
Release: 2014-11-05
ISBN 10: 331913650X
ISBN 13: 9783319136509
Language: EN, FR, DE, ES & NL

Nature Inspired Computation and Machine Learning Book Review:

The two-volume set LNAI 8856 and LNAI 8857 constitutes the proceedings of the 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, held in Tuxtla, Mexico, in November 2014. The total of 87 papers plus 1 invited talk presented in these proceedings were carefully reviewed and selected from 348 submissions. The first volume deals with advances in human-inspired computing and its applications. It contains 44 papers structured into seven sections: natural language processing, natural language processing applications, opinion mining, sentiment analysis, and social network applications, computer vision, image processing, logic, reasoning, and multi-agent systems, and intelligent tutoring systems. The second volume deals with advances in nature-inspired computation and machine learning and contains also 44 papers structured into eight sections: genetic and evolutionary algorithms, neural networks, machine learning, machine learning applications to audio and text, data mining, fuzzy logic, robotics, planning, and scheduling, and biomedical applications.

Metaheuristic Optimization Nature Inspired Algorithms Swarm and Computational Intelligence Theory and Applications

Metaheuristic Optimization  Nature Inspired Algorithms Swarm and Computational Intelligence  Theory and Applications
Author: Modestus O. Okwu,Lagouge K. Tartibu
Publsiher: Springer Nature
Total Pages: 192
Release: 2020-11-13
ISBN 10: 3030611116
ISBN 13: 9783030611118
Language: EN, FR, DE, ES & NL

Metaheuristic Optimization Nature Inspired Algorithms Swarm and Computational Intelligence Theory and Applications Book Review:

This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.

Nature Inspired Computation in Data Mining and Machine Learning

Nature Inspired Computation in Data Mining and Machine Learning
Author: Xin-She Yang,Xing-Shi He
Publsiher: Springer Nature
Total Pages: 273
Release: 2019-09-03
ISBN 10: 3030285537
ISBN 13: 9783030285531
Language: EN, FR, DE, ES & NL

Nature Inspired Computation in Data Mining and Machine Learning Book Review:

This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.

Advances in Brain Inspired Cognitive Systems

Advances in Brain Inspired Cognitive Systems
Author: Jinchang Ren,Amir Hussain,Jiangbin Zheng,Cheng-Lin Liu,Bin Luo,Huimin Zhao,Xinbo Zhao
Publsiher: Springer
Total Pages: 870
Release: 2018-10-05
ISBN 10: 3030005631
ISBN 13: 9783030005634
Language: EN, FR, DE, ES & NL

Advances in Brain Inspired Cognitive Systems Book Review:

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.

Neural Information Processing

Neural Information Processing
Author: Bao-Liang Lu,Liqing Zhang,James Kwok
Publsiher: Springer Science & Business Media
Total Pages: 778
Release: 2011-10-26
ISBN 10: 3642249574
ISBN 13: 9783642249570
Language: EN, FR, DE, ES & NL

Neural Information Processing Book Review:

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.

Time Space Spiking Neural Networks and Brain Inspired Artificial Intelligence

Time Space  Spiking Neural Networks and Brain Inspired Artificial Intelligence
Author: Nikola K. Kasabov
Publsiher: Springer
Total Pages: 738
Release: 2018-08-29
ISBN 10: 3662577151
ISBN 13: 9783662577158
Language: EN, FR, DE, ES & NL

Time Space Spiking Neural Networks and Brain Inspired Artificial Intelligence Book Review:

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.

Handbook of Research on Modeling Analysis and Application of Nature Inspired Metaheuristic Algorithms

Handbook of Research on Modeling  Analysis  and Application of Nature Inspired Metaheuristic Algorithms
Author: Dash, Sujata,Tripathy, B.K.,Rahman, Atta ur
Publsiher: IGI Global
Total Pages: 538
Release: 2017-08-10
ISBN 10: 152252858X
ISBN 13: 9781522528586
Language: EN, FR, DE, ES & NL

Handbook of Research on Modeling Analysis and Application of Nature Inspired Metaheuristic Algorithms Book Review:

The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems. The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.

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,Cesare Alippi,Yoonsuck Choe,Francesco Carlo Morabito
Publsiher: Academic Press
Total Pages: 352
Release: 2018-10-30
ISBN 10: 0128162503
ISBN 13: 9780128162507
Language: EN, FR, DE, ES & NL

Artificial Intelligence in the Age of Neural Networks and Brain Computing Book Review:

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

Medical Imaging

Medical Imaging
Author: K.C. Santosh,Sameer Antani,DS Guru,Nilanjan Dey
Publsiher: CRC Press
Total Pages: 238
Release: 2019-08-20
ISBN 10: 0429642490
ISBN 13: 9780429642494
Language: EN, FR, DE, ES & NL

Medical Imaging Book Review:

The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.

Brain Inspired Information Technology

Brain Inspired Information Technology
Author: Akitoshi Hanazawa,Tsutom Miki,Keiichi Horio
Publsiher: Springer Science & Business Media
Total Pages: 178
Release: 2010-09-22
ISBN 10: 3642040241
ISBN 13: 9783642040245
Language: EN, FR, DE, ES & NL

Brain Inspired Information Technology Book Review:

"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.

Bio inspired Neurocomputing

Bio inspired Neurocomputing
Author: Akash Kumar Bhoi,Pradeep Kumar Mallick,Chuan-Ming Liu,Valentina E. Balas
Publsiher: Springer Nature
Total Pages: 427
Release: 2020-07-21
ISBN 10: 9811554951
ISBN 13: 9789811554957
Language: EN, FR, DE, ES & NL

Bio inspired Neurocomputing Book Review:

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.

Advances in Brain Inspired Cognitive Systems

Advances in Brain Inspired Cognitive Systems
Author: Jinchang Ren,Amir Hussain,Huimin Zhao,Kaizhu Huang,Jiangbin Zheng,Jun Cai,Rongjun Chen,Yinyin Xiao
Publsiher: Springer Nature
Total Pages: 595
Release: 2020-01-31
ISBN 10: 303039431X
ISBN 13: 9783030394318
Language: EN, FR, DE, ES & NL

Advances in Brain Inspired Cognitive Systems Book Review:

This book constitutes the refereed proceedings of the 10th International Conference on Advances in Brain Inspired Cognitive Systems, BICS 2019, held in Guangzhou, China, in July 2019. The 57 papers presented in this volume were carefully reviewed and selected from 129 submissions. The papers are organized in topical sections named: neural computation; biologically inspired systems; image recognition: detection, tracking and classification; and data analysis and natural language processing.

Advances in Nature Inspired Computing and Applications

Advances in Nature Inspired Computing and Applications
Author: Shishir Kumar Shandilya,Smita Shandilya,Atulya K. Nagar
Publsiher: Springer
Total Pages: 349
Release: 2018-08-29
ISBN 10: 3319964518
ISBN 13: 9783319964515
Language: EN, FR, DE, ES & NL

Advances in Nature Inspired Computing and Applications Book Review:

This book contains research contributions from leading global scholars in nature-inspired computing. It includes comprehensive coverage of each respective topic, while also highlighting recent and future trends. The contributions provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application. This book has focus on the current researches while highlighting the empirical results along with theoretical concepts to provide a comprehensive reference for students, researchers, scholars, professionals and practitioners in the field of Advanced Artificial Intelligence, Nature-Inspired Algorithms and Soft Computing.

Advances in Natural Computation

Advances in Natural Computation
Author: Licheng Jiao,Lipo Wang,Xinbo Gao,Jing Liu,Feng Wu
Publsiher: Springer Science & Business Media
Total Pages: 992
Release: 2006-09-19
ISBN 10: 3540459014
ISBN 13: 9783540459019
Language: EN, FR, DE, ES & NL

Advances in Natural Computation Book Review:

This is volume I of the proceedings of the Second International Conference on Natural Computation, ICNC 2006. After a demanding review process 168 carefully revised full papers and 86 revised short papers were selected from 1915 submissions for presentation in two volumes. This first volume includes 130 papers related to artificial neural networks, natural neural systems and cognitive science, neural network applications, as well as evolutionary computation: theory and algorithms.

Handbook of Neural Computation

Handbook of Neural Computation
Author: Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas
Publsiher: Academic Press
Total Pages: 658
Release: 2017-07-18
ISBN 10: 0128113197
ISBN 13: 9780128113196
Language: EN, FR, DE, ES & NL

Handbook of Neural Computation Book Review:

Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

System and Circuit Design for Biologically Inspired Intelligent Learning

System and Circuit Design for Biologically Inspired Intelligent Learning
Author: Temel, Turgay
Publsiher: IGI Global
Total Pages: 412
Release: 2010-10-31
ISBN 10: 1609600207
ISBN 13: 9781609600204
Language: EN, FR, DE, ES & NL

System and Circuit Design for Biologically Inspired Intelligent Learning Book Review:

"The objective of the book is to introduce and bring together well-known circuit design aspects, as well as to cover up-to-date outcomes of theoretical studies in decision-making, biologically-inspired, and artificial intelligent learning techniques"--Provided by publisher.

Cortex inspired Developmental Learning for Vision based Navigation Attention and Recognition

Cortex inspired Developmental Learning for Vision based Navigation  Attention and Recognition
Author: Zhengping Ji
Publsiher: Anonim
Total Pages: 304
Release: 2009
ISBN 10:
ISBN 13: MSU:31293030631067
Language: EN, FR, DE, ES & NL

Cortex inspired Developmental Learning for Vision based Navigation Attention and Recognition Book Review: