Intelligence Science and Big Data Engineering Big Data and Machine Learning Techniques

Intelligence Science and Big Data Engineering  Big Data and Machine Learning Techniques
Author: Xiaofei He,Xinbo Gao,Yanning Zhang,Zhi-Hua Zhou,Zhi-Yong Liu,Baochuan Fu,Fuyuan Hu,Zhancheng Zhang
Publsiher: Springer
Total Pages: 627
Release: 2015-10-27
Genre: Computers
ISBN: 3319238612

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The two-volume set LNCS 9242 + 9243 constitutes the proceedings of the 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, held in Suzhou, China, in June 2015. The total of 126 papers presented in the proceedings was carefully reviewed and selected from 416 submissions. They deal with big data, neural networks, image processing, computer vision, pattern recognition and graphics, object detection, dimensionality reduction and manifold learning, unsupervised learning and clustering, anomaly detection, semi-supervised learning.

Intelligence Science and Big Data Engineering

Intelligence Science and Big Data Engineering
Author: Yuxin Peng,Kai Yu,Jiwen Lu,Xingpeng Jiang
Publsiher: Springer
Total Pages: 685
Release: 2018-11-08
Genre: Computers
ISBN: 9783030026981

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This book constitutes the proceedings of the 8th International Conference on Intelligence Science and Big DataEngineering, IScIDE 2018, held in Lanzhou, China, in August 2018.The 59 full papers presented in this book were carefully reviewed and selected from 121 submissions.They are grouped in topical sections on robots and intelligent systems; statistics and learning; deep learning; objects and language; classification and clustering; imaging; and biomedical signal processing.​

Intelligence Science and Big Data Engineering

Intelligence Science and Big Data Engineering
Author: Changyin Sun,Fang Fang,Zhi-Hua Zhou,Wankou Yang,Zhiyong Liu
Publsiher: Springer
Total Pages: 908
Release: 2013-11-18
Genre: Computers
ISBN: 9783642420573

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This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013, held in Beijing, China, in July/August 2013. The 111 papers presented were carefully peer-reviewed and selected from 390 submissions. Topics covered include information theoretic and Bayesian approaches; probabilistic graphical models; pattern recognition and computer vision; signal processing and image processing; machine learning and computational intelligence; neural networks and neuro-informatics; statistical inference and uncertainty reasoning; bioinformatics and computational biology and speech recognition and natural language processing.

Intelligence Science and Big Data Engineering

Intelligence Science and Big Data Engineering
Author: Yi Sun,Huchuan Lu,Lihe Zhang,Jian Yang,Hua Huang
Publsiher: Springer
Total Pages: 689
Release: 2017-09-14
Genre: Computers
ISBN: 9783319677774

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This book constitutes the proceedings of the 7th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2017, held in Dalian, China, in September 2017.The 48 full papers and 14 short papers presented in this volume were carefully reviewed and selected from 121 submissions. They deal with statistics and learning; deep neural networks; faces and people; objects; classification and clustering; imaging; biomedical signal processing; and recommendation.

Intelligence Science and Big Data Engineering Visual Data Engineering

Intelligence Science and Big Data Engineering  Visual Data Engineering
Author: Zhen Cui,Jinshan Pan,Shanshan Zhang,Liang Xiao,Jian Yang
Publsiher: Springer Nature
Total Pages: 577
Release: 2019-11-28
Genre: Computers
ISBN: 9783030361891

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The two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019. The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning.

Intelligence Science and Big Data Engineering Image and Video Data Engineering

Intelligence Science and Big Data Engineering  Image and Video Data Engineering
Author: Xiaofei He,Xinbo Gao,Yanning Zhang,Zhi-Hua Zhou,Zhi-Yong Liu,Baochuan Fu,Fuyuan Hu,Zhancheng Zhang
Publsiher: Springer
Total Pages: 661
Release: 2015-10-13
Genre: Computers
ISBN: 9783319239897

Download Intelligence Science and Big Data Engineering Image and Video Data Engineering Book in PDF, Epub and Kindle

The two-volume set LNCS 9242 + 9243 constitutes the proceedings of the 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, held in Suzhou, China, in June 2015. The total of 126 papers presented in the proceedings was carefully reviewed and selected from 416 submissions. They deal with big data, neural networks, image processing, computer vision, pattern recognition and graphics, object detection, dimensionality reduction and manifold learning, unsupervised learning and clustering, anomaly detection, semi-supervised learning.

Intelligence Science and Big Data Engineering Big Data and Machine Learning

Intelligence Science and Big Data Engineering  Big Data and Machine Learning
Author: Zhen Cui,Jinshan Pan,Shanshan Zhang,Liang Xiao,Jian Yang
Publsiher: Springer Nature
Total Pages: 455
Release: 2019-11-28
Genre: Computers
ISBN: 9783030362041

Download Intelligence Science and Big Data Engineering Big Data and Machine Learning Book in PDF, Epub and Kindle

The two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019. The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning.

Intelligence Science and Big Data Engineering Big Data and Machine Learning Techniques

Intelligence Science and Big Data Engineering  Big Data and Machine Learning Techniques
Author: Xiaofei He,Xinbo Gao,Yanning Zhang,Zhi-Hua Zhou,Zhi-Yong Liu,Baochuan Fu,Fuyuan Hu,Zhancheng Zhang
Publsiher: Springer
Total Pages: 627
Release: 2015-10-13
Genre: Computers
ISBN: 9783319238623

Download Intelligence Science and Big Data Engineering Big Data and Machine Learning Techniques Book in PDF, Epub and Kindle

The two-volume set LNCS 9242 + 9243 constitutes the proceedings of the 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, held in Suzhou, China, in June 2015. The total of 126 papers presented in the proceedings was carefully reviewed and selected from 416 submissions. They deal with big data, neural networks, image processing, computer vision, pattern recognition and graphics, object detection, dimensionality reduction and manifold learning, unsupervised learning and clustering, anomaly detection, semi-supervised learning.

Advances in Artificial Intelligence and Data Engineering

Advances in Artificial Intelligence and Data Engineering
Author: Niranjan N. Chiplunkar,Takanori Fukao
Publsiher: Springer Nature
Total Pages: 1475
Release: 2020-08-13
Genre: Technology & Engineering
ISBN: 9789811535147

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This book presents selected peer-reviewed papers from the International Conference on Artificial Intelligence and Data Engineering (AIDE 2019). The topics covered are broadly divided into four groups: artificial intelligence, machine vision and robotics, ambient intelligence, and data engineering. The book discusses recent technological advances in the emerging fields of artificial intelligence, machine learning, robotics, virtual reality, augmented reality, bioinformatics, intelligent systems, cognitive systems, computational intelligence, neural networks, evolutionary computation, speech processing, Internet of Things, big data challenges, data mining, information retrieval, and natural language processing. Given its scope, this book can be useful for students, researchers, and professionals interested in the growing applications of artificial intelligence and data engineering.

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications
Author: Arun Kumar Sangaiah,Zhiyong Zhang,Michael Sheng
Publsiher: Academic Press
Total Pages: 362
Release: 2018-08-21
Genre: Technology & Engineering
ISBN: 9780128133279

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Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering. It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful. Presents a brief overview of computational intelligence paradigms and its significant role in application domains Illustrates the state-of-the-art and recent developments in the new theories and applications of CI approaches Familiarizes the reader with computational intelligence concepts and technologies that are successfully used in the implementation of cloud-centric multimedia services in massive data processing Provides new advances in the fields of CI for bio-engineering application

Recent Advances in Artificial Intelligence and Data Engineering

Recent Advances in Artificial Intelligence and Data Engineering
Author: Pushparaj Shetty D.,Surendra Shetty
Publsiher: Springer Nature
Total Pages: 463
Release: 2021-12-02
Genre: Computers
ISBN: 9789811633423

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This book presents select proceedings of the International Conference on Artificial Intelligence and Data Engineering (AIDE 2020). Various topics covered in this book include deep learning, neural networks, machine learning, computational intelligence, cognitive computing, fuzzy logic, expert systems, brain-machine interfaces, ant colony optimization, natural language processing, bioinformatics and computational biology, cloud computing, machine vision and robotics, ambient intelligence, intelligent transportation, sensing and sensor networks, big data challenge, data science, high performance computing, data mining and knowledge discovery, and data privacy and security. The book will be a valuable reference for beginners, researchers, and professionals interested in artificial intelligence, robotics and data engineering.

Artificial Intelligence Machine Learning and Data Science Technologies

Artificial Intelligence  Machine Learning  and Data Science Technologies
Author: Neeraj Mohan
Publsiher: CRC Press
Total Pages: 297
Release: 2021-10
Genre: Artificial intelligence
ISBN: 0367720922

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"This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, etc. and how all countries around the world are feeling this impact. The book aims at low cost solutions which could be implemented even in developing countries. It highlights the significant impact these technologies have on various industries and on us as humans. It provides a virtual picture of forthcoming better human life shadowed by the new technologies and their applications and discusses the impact Data Science has on business applications. The book will also include an overview of the different AI applications and their correlation between each other. The audience is graduate and post graduate students, researchers, academicians, institutions, and professionals that are interested in exploring key technologies like Artificial Intelligence, Machine Learning, and Data Science"--

Data Science and Big Data An Environment of Computational Intelligence

Data Science and Big Data  An Environment of Computational Intelligence
Author: Witold Pedrycz,Shyi-Ming Chen
Publsiher: Springer
Total Pages: 303
Release: 2017-03-21
Genre: Technology & Engineering
ISBN: 9783319534749

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This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration and business.Data science and big data go hand in hand and constitute a rapidly growing area of research and have attracted the attention of industry and business alike. The area itself has opened up promising new directions of fundamental and applied research and has led to interesting applications, especially those addressing the immediate need to deal with large repositories of data and building tangible, user-centric models of relationships in data. Data is the lifeblood of today’s knowledge-driven economy.Numerous data science models are oriented towards end users and along with the regular requirements for accuracy (which are present in any modeling), come the requirements for ability to process huge and varying data sets as well as robustness, interpretability, and simplicity (transparency). Computational intelligence with its underlying methodologies and tools helps address data analytics needs.The book is of interest to those researchers and practitioners involved in data science, Internet engineering, computational intelligence, management, operations research, and knowledge-based systems.

Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry

Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry
Author: Chkoniya, Valentina
Publsiher: IGI Global
Total Pages: 653
Release: 2021-06-25
Genre: Computers
ISBN: 9781799869863

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The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.

Trends in Data Engineering Methods for Intelligent Systems

Trends in Data Engineering Methods for Intelligent Systems
Author: Jude Hemanth,Tuncay Yigit,Bogdan Patrut,Anastassia Angelopoulou
Publsiher: Springer Nature
Total Pages: 773
Release: 2021-07-05
Genre: Computers
ISBN: 9783030793579

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This book briefly covers internationally contributed chapters with artificial intelligence and applied mathematics-oriented background-details. Nowadays, the world is under attack of intelligent systems covering all fields to make them practical and meaningful for humans. In this sense, this edited book provides the most recent research on use of engineering capabilities for developing intelligent systems. The chapters are a collection from the works presented at the 2nd International Conference on Artificial Intelligence and Applied Mathematics in Engineering held within 09-10-11 October 2020 at the Antalya, Manavgat (Turkey). The target audience of the book covers scientists, experts, M.Sc. and Ph.D. students, post-docs, and anyone interested in intelligent systems and their usage in different problem domains. The book is suitable to be used as a reference work in the courses associated with artificial intelligence and applied mathematics.