Intelligence in big data technologies -- beyond the hype : proceedings of ICBDCC 2019 / editors, J. Dinesh Peter, Steven L. Fernandes, Amir H. Alavi.

Format
Book
Language
English
Εdition
1st edition 2021.
Published/​Created
Singapore : Springer Singapore : Imprint: Springer, 2021.
Description
1 online resource (xiii, 636 pages) : illustrations

Details

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Editor
Related name
Series
Summary note
This book is a compendium of the proceedings of the International Conference on Big-Data and Cloud Computing. The papers discuss the recent advances in the areas of big data analytics, data analytics in cloud, smart cities and grid, etc. This volume primarily focuses on the application of knowledge which promotes ideas for solving problems of the society through cutting-edge big-data technologies. The essays featured in this proceeding provide novel ideas that contribute for the growth of world class research and development. It will be useful to researchers in the area of advanced engineering sciences.
Notes
Includes index.
Contents
  • From Dew Over Cloud towards the Rainbow Ecosystem of the Future:Nature – Human – Machine
  • L1 Norm SVD based Ranking Scheme: A Novel Method in Big Data Mining
  • Human Annotation and Emotion Recognition for Counseling System with Cloud Environment using Deep Learning
  • Enhancing Intricate details of ultrasound PCOD scan images using Tailored Anisotropic Diffusion Filter (TADF)
  • LSTM and GRU Deep learning Architectures for Smoke Prediction System in Indoor Environment
  • A mobile based framework for detecting objects using SSD-Mobilenet in indoor environment
  • Privacy Preserving Big Data Publication: (K, L) Anonymity
  • Comparative Analysis of the efficacy of the EEG based Machine Learning method for the screening and diagnosing of Alcohol Use Disorder (AUD)
  • Smart solution for waste management: a coherent framework based on IoT and big data analytics
  • Early detection of diabetes from daily routine activities: Predictive modeling based on machine learning techniques.
ISBN
981-15-5285-1
Doi
  • 10.1007/978-981-15-5285-4
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