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Springer Intelligent Data Analysis for COVID-19 Pandemic (Algorithms for Intelligent Systems)

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Description

This book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details. From the Back Cover This book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details. About the Author Dr. Niranjanamurthy M is Assistant Professor, Department of Computer Applications, M S Ramaiah Institute of Technology, Bangalore, Karnataka, India. He completed Ph.D. in Computer Science at JJTU, Rajasthan (2016); M.Phil. in Computer Science at VMU, Salem (2009); Masters in Computer Applications at Visvesvaraiah Technological University, Belgaum, Karnataka (2007);   BCA from Kuvempu University 2004 with University 5th Rank. He has 10 years of teaching experience and 2 years of industry experience as Software Engineer. He has published books in Scholars Press Germany and CRC Press. He also published 56 research papers and filed 12 patents. Currently, he is guiding four Ph.D. research scholars in the areas of data science, edge computing, ML, and networking. He is Reviewer of 22 international journals and Series Editor in CRC Press and Scrivener Publishing. He has received best research journal reviewer and researcher awards. He is a member of IEEE, CSTA, IAENG, and INSC. His areas of interest are data science, ML, edge computing, software engineering, web services, cloud computing, and networking.   Dr. Siddhartha Bhattacharyya [LFOSI, LFISRD, FIET (UK), FIETE, FIE(I), SMIEEE, SMIETI, SMACM, LMCRSI, LMCSI, LMISTE, LMIUPRAI, LMCEGR, LMICCI, LMALI, MIRSS, MIAENG, MCSTA, MIAASSE, MIDES, MISSIP, MSDIWC] is currently serving as Professor in the Department of Computer Science and Engineering of Christ University, Bangalore. He is Co-Author of 5 books and Co-Editor of 75 books and has more than 300 research publications in international journals and conference proceedings to his credit. He has got two PCTs to his credit. He is Associate Editor of several reputed journals including Applied Soft Computing, IEEE Access, Evolutionary Intelligence, and IET Quantum Communications. He is Editor of International Journal of Pattern Recognition Research and  Founding Editor-in-Chief of International Journal of Hybrid Intelligence, Inderscience. His research interests include hybrid intelligence, pattern recognition, multimedia data processing, social networks, and quantum computing.    Dr. Neeraj Kumar is currently engaged with the Department of Information Technology, Babasaheb Bhimrao Ambedkar University (A Central University), Lucknow (India). He has completed his Doctorate in Information Technology from BBAU, Lucknow

Product Specifications

Format
Hardcover
Domain
Amazon UK
Release Date
23 June 2021
Listed Since
07 March 2021

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