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 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.

Intelligent Computing Theories and Methodologies

Intelligent Computing Theories and Methodologies
Author: De-Shuang Huang,Vitoantonio Bevilacqua,Prashan Premaratne
Publsiher: Springer
Total Pages: 755
Release: 2015-08-10
ISBN 10: 3319221809
ISBN 13: 9783319221809
Language: EN, FR, DE, ES & NL

Intelligent Computing Theories and Methodologies Book Review:

This two-volume set LNCS 9225 and LNCS 9226 constitutes - in conjunction with the volume LNAI 9227 - the refereed proceedings of the 11th International Conference on Intelligent Computing, ICIC 2015, held in Fuzhou, China, in August 2015. The total of 191 full and 42 short papers presented in the three ICIC 2015 volumes was carefully reviewed and selected from 671 submissions. The papers are organized in topical sections such as evolutionary computation and learning; compressed sensing, sparse coding and social computing; neural networks, nature inspired computing and optimization; pattern recognition and signal processing; image processing; biomedical informatics theory and methods; differential evolution, particle swarm optimization and niche technology; intelligent computing and knowledge discovery and data mining; soft computing and machine learning; computational biology, protein structure and function prediction; genetic algorithms; artificial bee colony algorithms; swarm intelligence and optimization; social computing; information security; virtual reality and human-computer interaction; healthcare informatics theory and methods; unsupervised learning; collective intelligence; intelligent computing in robotics; intelligent computing in communication networks; intelligent control and automation; intelligent data analysis and prediction; gene expression array analysis; gene regulation modeling and analysis; protein-protein interaction prediction; biology inspired computing and optimization; analysis and visualization of large biological data sets; motif detection; biomarker discovery; modeling; simulation; and optimization of biological systems; biomedical data modeling and mining; intelligent computing in biomedical signal/image analysis; intelligent computing in brain imaging; neuroinformatics; cheminformatics; intelligent computing in computational biology; computational genomics; special session on biomedical data integration and mining in the era of big data; special session on big data analytics; special session on artificial intelligence for ambient assisted living; and special session on swarm intelligence with discrete dynamics.

Nature Inspired Problem Solving Methods in Knowledge Engineering

Nature Inspired Problem Solving Methods in Knowledge Engineering
Author: José Mira,José R. Álvarez
Publsiher: Springer
Total Pages: 650
Release: 2007-06-23
ISBN 10: 3540730559
ISBN 13: 9783540730552
Language: EN, FR, DE, ES & NL

Nature Inspired Problem Solving Methods in Knowledge Engineering Book Review:

The second of a two-volume set, this book constitutes the refereed proceedings of the Second International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2007, held in La Manga del Mar Menor, Spain in June 2007. It contains all the contributions connected with biologically inspired methods and techniques for solving AI and knowledge engineering problems in different application domains.

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.

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.

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

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.

The Deep Learning Revolution

The Deep Learning Revolution
Author: Terrence J. Sejnowski
Publsiher: MIT Press
Total Pages: 352
Release: 2018-10-23
ISBN 10: 026203803X
ISBN 13: 9780262038034
Language: EN, FR, DE, ES & NL

The Deep Learning Revolution Book Review:

How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

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

Bio Inspired Systems Computational and Ambient Intelligence

Bio Inspired Systems  Computational and Ambient Intelligence
Author: Joan Cabestany,Francisco Sandoval,Alberto Prieto,Juan M. Corchado,Juan Manuel Corchado Rodríguez
Publsiher: Springer Science & Business Media
Total Pages: 1356
Release: 2009-06-08
ISBN 10: 3642024777
ISBN 13: 9783642024771
Language: EN, FR, DE, ES & NL

Bio Inspired Systems Computational and Ambient Intelligence Book Review:

This book constitutes the refereed proceedings of the 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, held in Salamanca, Spain in June 2009. The 167 revised full papers presented together with 3 invited lectures were carefully reviewed and selected from over 230 submissions. The papers are organized in thematic sections on theoretical foundations and models; learning and adaptation; self-organizing networks, methods and applications; fuzzy systems; evolutionary computation and genetic algoritms; pattern recognition; formal languages in linguistics; agents and multi-agent on intelligent systems; brain-computer interfaces (bci); multiobjetive optimization; robotics; bioinformatics; biomedical applications; ambient assisted living (aal) and ambient intelligence (ai); other applications.

Computational Vision and Bio Inspired Computing

Computational Vision and Bio Inspired Computing
Author: S. Smys,João Manuel R. S. Tavares,Valentina Emilia Balas,Abdullah M. Iliyasu
Publsiher: Springer Nature
Total Pages: 1413
Release: 2020-01-06
ISBN 10: 3030372189
ISBN 13: 9783030372187
Language: EN, FR, DE, ES & NL

Computational Vision and Bio Inspired Computing Book Review:

This proceedings book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. Due to the rapid advances in the emerging information, communication and computing technologies, the Internet of Things, cloud and edge computing, and artificial intelligence play a significant role in the computational vision context. In recent years, computational vision has contributed to enhancing the methods of controlling the operations in biological systems, like ant colony optimization, neural networks, and immune systems. Moreover, the ability of computational vision to process a large number of data streams by implementing new computing paradigms has been demonstrated in numerous studies incorporating computational techniques in the emerging bio-inspired models. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization, and big data modeling and management, that make use of effectual computing processes in the bio-inspired systems. As such it contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems, and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.

Applied Nature Inspired Computing Algorithms and Case Studies

Applied Nature Inspired Computing  Algorithms and Case Studies
Author: Nilanjan Dey,Amira S. Ashour,Siddhartha Bhattacharyya
Publsiher: Springer
Total Pages: 275
Release: 2019-08-10
ISBN 10: 9811392633
ISBN 13: 9789811392634
Language: EN, FR, DE, ES & NL

Applied Nature Inspired Computing Algorithms and Case Studies Book Review:

This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each. Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.

Bio inspired Computing Models And Algorithms

Bio inspired Computing Models And Algorithms
Author: Song Tao,Zheng Pan,Wong Dennis Mou Ling,Wang Xun
Publsiher: World Scientific
Total Pages: 300
Release: 2019-04-08
ISBN 10: 9813143193
ISBN 13: 9789813143197
Language: EN, FR, DE, ES & NL

Bio inspired Computing Models And Algorithms Book Review:

Bio-inspired computing (BIC) focuses on the designs and developments of computer algorithms and models based on biological mechanisms and living phenomena. It is now a major subfield of natural computation that leverages on the recent advances in computer science, biology and mathematics.The ideas provide abundant inspiration to construct high-performance computing models and intelligent algorithms, thus enabling powerful tools to solve real-life problems.Written by world-renowned researchers, this compendium covers the most influential topics on BIC, where the newly-obtained algorithms, developments and results are introduced and elaborated. The potential and valuable directions for further research are addressed as well.

Swarm Intelligence and Bio Inspired Computation

Swarm Intelligence and Bio Inspired Computation
Author: Xin-She Yang,Zhihua Cui,Renbin Xiao,Amir Hossein Gandomi,Mehmet Karamanoglu
Publsiher: Newnes
Total Pages: 450
Release: 2013-05-16
ISBN 10: 0124051774
ISBN 13: 9780124051775
Language: EN, FR, DE, ES & NL

Swarm Intelligence and Bio Inspired Computation Book Review:

Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers. Focuses on the introduction and analysis of key algorithms Includes case studies for real-world applications Contains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.

Applications of Evolutionary Computation

Applications of Evolutionary Computation
Author: Kevin Sim,Paul Kaufmann
Publsiher: Springer
Total Pages: 917
Release: 2018-03-07
ISBN 10: 3319775383
ISBN 13: 9783319775388
Language: EN, FR, DE, ES & NL

Applications of Evolutionary Computation Book Review:

This book constitutes the refereed conference proceedings of the 21st International Conference on the Applications of Evolutionary Computation, EvoApplications 2018, held in Parma, Italy, in April 2018, collocated with the Evo* 2018 events EuroGP, EvoCOP, and EvoMUSART. The 59 revised full papers presented were carefully reviewed and selected from 84 submissions. EvoApplications 2018 combined research from 14 different domains: business analytics and finance (EvoBAFIN); computational biology (EvoBIO); communication networks and other parallel and distributed systems (EvoCOMNET); complex systems (EvoCOMPLEX); energy-related optimization (EvoENERGY); games and multi-agent systems (EvoGAMES); image analysis, signal processing and pattern recognition (EvoIASP); realworld industrial and commercial environments (EvoINDUSTRY); knowledge incorporation in evolutionary computation (EvoKNOW); continuous parameter optimization (EvoNUM); parallel architectures and distributed infrastructures (EvoPAR); evolutionary robotics (EvoROBOT); nature-inspired algorithms in software engineering and testing (EvoSET); and stochastic and dynamic environments (EvoSTOC).

Cognitive Neuroscience of Memory Consolidation

Cognitive Neuroscience of Memory Consolidation
Author: Nikolai Axmacher,Björn Rasch
Publsiher: Springer
Total Pages: 417
Release: 2017-02-09
ISBN 10: 3319450662
ISBN 13: 9783319450667
Language: EN, FR, DE, ES & NL

Cognitive Neuroscience of Memory Consolidation Book Review:

This edited volume provides an overview the state-of-the-art in the field of cognitive neuroscience of memory consolidation. In a number of sections, the editors collect contributions of leading researchers . The topical focus lies on current issues of interest such as memory consolidation including working and long-term memory. In particular, the role of sleep in relation to memory consolidation will be addressed. The target audience primarily comprises research experts in the field of cognitive neuroscience but the book may also be beneficial for graduate students.

Advances in Natural Computation

Advances in Natural Computation
Author: Lipo Wang,Ke Chen
Publsiher: Springer Science & Business Media
Total Pages: 1292
Release: 2005-08-17
ISBN 10: 3540283250
ISBN 13: 9783540283256
Language: EN, FR, DE, ES & NL

Advances in Natural Computation Book Review:

The three volume set LNCS 3610, LNCS 3611, and LNCS 3612 constitutes the refereed proceedings of the First International Conference on Natural Computation, ICNC 2005, held in Changsha, China, in August 2005 jointly with the Second International Conference on Fuzzy Systems and Knowledge Discovery FSKD 2005 (LNAI volumes 3613 and 3614).The program committee selected 313 carefully revised full papers and 189 short papers for presentation in three volumes from 1887 submissions. The first volume includes all the contributions related to learning algorithms and architectures in neural networks, neurodynamics, statistical neural network models and support vector machines, and other topics in neural network models; cognitive science, neuroscience informatics, bioinformatics, and bio-medical engineering, and neural network applications as communications and computer networks, expert system and informatics, and financial engineering. The second volume concentrates on neural network applications such as pattern recognition and diagnostics, robotics and intelligent control, signal processing and multi-media, and other neural network applications; evolutionary learning, artificial immune systems, evolutionary theory, membrane, molecular, DNA computing, and ant colony systems. The third volume deals with evolutionary methodology, quantum computing, swarm intelligence and intelligent agents; natural computation applications as bioinformatics and bio-medical engineering, robotics and intelligent control, and other applications of natural computation; hardware implementations of natural computation, and fuzzy neural systems as well as soft computing.

Handbook of Nature Inspired and Innovative Computing

Handbook of Nature Inspired and Innovative Computing
Author: Albert Y. Zomaya
Publsiher: Springer Science & Business Media
Total Pages: 736
Release: 2006-01-10
ISBN 10: 9780387405322
ISBN 13: 0387405321
Language: EN, FR, DE, ES & NL

Handbook of Nature Inspired and Innovative Computing Book Review:

As computing devices proliferate, demand increases for an understanding of emerging computing paradigms and models based on natural phenomena. Neural networks, evolution-based models, quantum computing, and DNA-based computing and simulations are all a necessary part of modern computing analysis and systems development. Vast literature exists on these new paradigms and their implications for a wide array of applications. This comprehensive handbook, the first of its kind to address the connection between nature-inspired and traditional computational paradigms, is a repository of case studies dealing with different problems in computing and solutions to these problems based on nature-inspired paradigms. The "Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies" is an essential compilation of models, methods, and algorithms for researchers, professionals, and advanced-level students working in all areas of computer science, IT, biocomputing, and network engineering.

Deep Learning and Neural Networks Concepts Methodologies Tools and Applications

Deep Learning and Neural Networks  Concepts  Methodologies  Tools  and Applications
Author: Management Association, Information Resources
Publsiher: IGI Global
Total Pages: 1671
Release: 2019-10-11
ISBN 10: 1799804151
ISBN 13: 9781799804154
Language: EN, FR, DE, ES & NL

Deep Learning and Neural Networks Concepts Methodologies Tools and Applications Book Review:

Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in various real-world applications such as computer vision, image processing, and pattern recognition. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications is a vital reference source that trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. It also explores the latest concepts, algorithms, and techniques of deep learning and data mining and analysis. Highlighting a range of topics such as natural language processing, predictive analytics, and deep neural networks, this multi-volume book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of deep learning.