Deep Learning Innovations and Their Convergence With Big Data

Deep Learning Innovations and Their Convergence With Big Data

S. Karthik (SNS College of Technology, Anna University, India), Anand Paul (Kyungpook National University, South Korea) and N. Karthikeyan (Mizan-Tepi University, Ethiopia)
Indexed In: SCOPUS
Release Date: July, 2017|Copyright: © 2018 |Pages: 265
ISBN13: 9781522530152|ISBN10: 1522530150|EISBN13: 9781522530169|DOI: 10.4018/978-1-5225-3015-2

Description

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.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Deep Auto-Encoders
  • Deep Neural Network
  • Domain Adaptation Modeling
  • Multilayer Perceptron (MLP)
  • Natural Language Processing (NLP)
  • Restricted Boltzmann Machines (RBM)
  • Threat Detection

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

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.

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