Machine Learning for Big Data Analysis /

Machine Learning for Big Data Analysis / / ed. by Siddhartha Bhattacharyya, Hrishikesh Bhaumik, Anirban Mukherjee, Sourav De.

This volume comprises six well-versed contributed chapters devoted to report the latest fi ndings on the applications of machine learning for big data analytics. Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal...

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Superior document:Title is part of eBook package: De Gruyter DG Plus DeG Package 2019 Part 1
MitwirkendeR:
Adate, Amit,
Bhattacharyya, Siddhartha,
Bhaumik, Hrishikesh,
Bick, Markus,
Blesik, Till,
Chakraborty, Susanta,
Choudhury, Abantika,
Deb, Moumita,
Gorbachev, S. V.,
Henesey, Lawrence,
Ho, Chiung Ching,
Mishra, Deepak,
Murawski, Matthias,
Nirala, Satish,
Ponraj, D. Narain,
Sagayam, K. Martin,
Sur, Surangam,
Tripathy, B. K.,
Vasanth, X. Ajay,
Vurucu, Murat,
HerausgeberIn:
Bhattacharyya, Siddhartha,
Bhaumik, Hrishikesh,
De, Sourav,
Mukherjee, Anirban,
Place / Publishing House:Berlin ;, Boston : : De Gruyter, , [2018]
©2019
Year of Publication:2018
Language:English
Series:De Gruyter Frontiers in Computational Intelligence , 1
Online Access:
Physical Description:1 online resource (X, 183 p.)
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Table of Contents:
  • Frontmatter
  • Preface
  • Contents
  • 1. Applying big data analytics to psychometric micro-targeting
  • 2. Keyframe selection for video indexing using an approximate minimal spanning tree
  • 3. Deep learning techniques for image processing
  • 4. Connecting cities using smart transportation: an overview
  • 5. Model of intellectual analysis of multidimensional semi-structured data based on deep neuro-fuzzy networks
  • 6. Image fusion in remote sensing based on sparse sampling method and PCNN techniques
  • Index

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