Deep Learning Innovations and Their Convergence With Big Data

S. Karthik

ISBN 10: 1522530150 / ISBN 13: 9781522530152

Published by Information Science Reference, 2017

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - The expansion of digital data has transformed various sectors of business such as healthcare, industrial manufacturing, and transportation. A new way of solving business problems has emerged through the use of machine learning techniques in conjunction with big data analytics. Deep Learning Innovations and Their Convergence With Big Data is a pivotal reference for the latest scholarly research on upcoming trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. Featuring extensive coverage on a broad range of topics and perspectives such as deep neural network, domain adaptation modeling, and threat detection, this book is ideally designed for researchers, professionals, and students seeking current research on the latest trends in the field of deep learning techniques in big data analytics.

Seller Inventory # 9781522530152

Bibliographic Details

• Title: Deep Learning Innovations and Their Convergence With Big Data
• Publisher: Information Science Reference
• Publication Date: 2017
• Language: English
• ISBN 10: 1522530150
• ISBN 13: 9781522530152
• Binding: Buch
• Condition: Neu
• Dimensions: 260W x 183H x 20D millimeters 260 millimeters width by 183 millimeters height by 20 millimeters depth
• Weight: 748 grams

About this title

Synopsis

"This book capture the state of the art trends and advancements in big data analytics, its technologies, and applications. The book also aims to identify potential research directions and technologies that will facilitate insight generation in various domains of science, industry, business, and consumer applications"--

About the Author

Anand Paul is currently working in The School of Computer Science and Engineering, Kyungpook National University, South Korea as Assistant Professor. He got his Ph.D. degree in the electrical engineering at National Cheng Kung University, Taiwan, R.O.C. in 2010. His research interests include Algorithm and Architecture Reconfigurable Embedded Computing. He is a delegate representing South Korea for M2M focus group and for MPEG. 2004-2010 he has been awarded Outstanding International Student Scholarship, and in 2009 he won the best paper award in national computer symposium, Taipei, Taiwan. He serves as a reviewer for IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transaction on System, Man and Cybernetics, IEEE Sensors, ACM Transactions on Embedded Computing Systems, IET Image Processing, IET Signal Processing and IET Circuits and Systems He gave invited talk in International Symposium on Embedded Technology workshop in 2012, He will be the track chair for Smart human computer interaction in ACM SAC 2014, and upcoming ACM SAC 2015. He is also an MPEG Delegate representing South Korea.