Overview
- Discusses novel theories and researched working models on data analytics and learning
- Focuses on current advances in data structuring and processing
- Serves as a reference for researchers as well as practitioners
Part of the book series: Lecture Notes in Networks and Systems (LNNS, volume 43)
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Table of contents (37 papers)
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Front Matter
Keywords
About this book
This book presents new theories and working models in the area of data analytics and learning. The papers included in this volume were presented at the first International Conference on Data Analytics and Learning (DAL 2018), which was hosted by the Department of Studies in Computer Science, University of Mysore, India on 30–31 March 2018. The areas covered include pattern recognition, image processing, deep learning, computer vision, data analytics, machine learning, artificial intelligence, and intelligent systems. As such, the book offers a valuable resource for researchers and practitioners alike.
Editors and Affiliations
About the editors
D. S. Guru is a Professor at the Department of Studies in Computer Science, University of Mysore. He completed his Doctorate in Computer Science from the University of Mysore in 2000, and has published more than 200 research papers in national and international journals and conference proceedings. He served as a Program Chair for the 2009 International Conference on Signal and Image Processing in Mysore, and is currently a reviewer for the International Journal of Pattern Recognition Letters, Journal of Pattern Recognition, Journal of Document Analysis and Recognition, Journal of Image and Vision Computing, and IEEE Transactions on Neural Networks.
B.H. Shekhar is a Professor at the Department of Studies in Computer Science, Mangalore University, India. His research interests include pattern recognition, image processing, database systems, and algorithms. He is an active researcher and has published more than 100 papers in peer-reviewed journals and conferences. He was granted a DST-DAAD Fellowship in 2002 and was the principal investigator for many research projects funded by the DST-RFBR and UGC. He is also a member of many academic societies, e.g. the International Association for Pattern Recognition, IACSIT, and Indian Unit for Pattern Recognition and Artificial Intelligence. P. Nagabhushan is Director of the Indian Institute of Information Technology, Allahabad, Uttar Pradesh. He previously served as a Professor at the University of Mysore and Amrita University. His areas of specialization are pattern recognition, digital image analysis and processing, document image analysis and knowledge mining. He has published more than 500 papers in peer-reviewed journals and conferences in these areas. He has received research funding from various organizations, e.g. the DRDO, MHRD, AICTE, ICMR, UGC, UGC, UPE and SAP, and has more than 30 years of teaching experience. Y. H. Sharath Kumar is an Associate Professor at the Department of Information Science and Engineering, Maharaja Institute of Technology, Mysore. He received his M.Tech. in 2009 and his Ph.D. in 2014, both from the University of Mysore. His research interests include image and video processing, pattern recognition, sign video analysis, logo classification, biometrics, and precision agriculture. He has authored a number of papers in reputed journals and conference proceedings.Bibliographic Information
Book Title: Data Analytics and Learning
Book Subtitle: Proceedings of DAL 2018
Editors: P. Nagabhushan, D. S. Guru, B. H. Shekar, Y. H. Sharath Kumar
Series Title: Lecture Notes in Networks and Systems
DOI: https://doi.org/10.1007/978-981-13-2514-4
Publisher: Springer Singapore
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2019
Softcover ISBN: 978-981-13-2513-7Published: 05 November 2018
eBook ISBN: 978-981-13-2514-4Published: 04 November 2018
Series ISSN: 2367-3370
Series E-ISSN: 2367-3389
Edition Number: 1
Number of Pages: XVI, 454
Number of Illustrations: 115 b/w illustrations, 151 illustrations in colour
Topics: Computational Intelligence, Data Mining and Knowledge Discovery, Signal, Image and Speech Processing, Big Data