Overview
- Presents research works in the field of intelligent computing
- Explores both the theoretical and practical aspects of data-intensive computing
- Serves as a reference for researchers and practitioners in academia and industry
Part of the book series: Smart Innovation, Systems and Technologies (SIST, volume 267)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
This volume covers broad areas of Evolution in Computational Intelligence. The conference papers included herein presents both theoretical as well as practical aspects of different areas like ANN and genetic algorithms, human-computer interaction, intelligent control optimization, evolutionary computing, intelligent e-learning systems, machine learning, mobile computing, multi-agent systems, etc. The volume will also serve as a knowledge centre for students of post-graduate level in various engineering disciplines.
Similar content being viewed by others
Keywords
Table of contents (54 papers)
Editors and Affiliations
About the editors
Dr. Jinshan Tang is currently a professor in the College of Computing at Michigan Technological University. He received his Ph.D. degree from Beijing University of Posts and Telecommunications and postdoctoral training at Harvard Medical School and the National Institute of Health. His research covers wide areas related to image processing and imaging technologies. His specific research interests include machine learning, biomedical image analysis and biomedical imaging, biometrics, computer vision, and image understanding. He has obtained more than three million US dollars grants as a PI or Co-PI. He has published more than 110 refereed journals and conference papers. He has also served as a committee member at various international conferences. He is a senior member of IEEE and a co-chair of the Technical Committee on Information Assurance and Intelligent Multimedia-Mobile Communications, IEEE SMC Society. He serves/served as a editors or guest editors of more than 10 journals.
Suresh Chandra Satapathy is Ph. D in Computer Science, currently working as Professor and at KIIT (Deemed to be University), Bhubaneshwar, Odisha, India. He held the position of the National Chairman Div-V (Educational and Research) of Computer Society of India and is also a senior member of IEEE. He has been instrumental in organizing more than 20 International Conferences in India as Organizing Chair and edited more than 30 bookvolumes from Springer LNCS, AISC, LNEE, and SIST Series as Corresponding Editor. He is quite active in research in the areas of swarm intelligence, machine learning, data mining. He has developed a new optimization algorithm known as social group optimization (SGO) published in Springer Journal. He has delivered a number of Keynote address and Tutorials in his areas of expertise in various events in India. He has more than 100 publications in reputed journals and conference proceedings. He is in Editorial Board of IGI Global, Inderscience, Growing Science journals and also Guest Editor for Arabian Journal of Science and Engineering published by Springer.
Peter Peer is a full professor of computer science at the University of Ljubljana, Slovenia, where he heads the Computer Vision Laboratory, coordinates the double degree study program with the Kyungpook National University, South Korea, and serves as a vice-dean for economic affairs. He received his doctoral degree in computer science from the University of Ljubljana in 2003. Within his post-doctorate, he was an invited researcher at CEIT, San Sebastian, Spain. His research interests focus on biometrics and computer vision. He participated in several national and EU-funded R&D projects and published more than 100 research papers in leading international peer reviewed journals and conferences. He is co-organizer of the Unconstrained Ear Recognition Challenge and Sclera Segmentation Benchmarking Competition. He serves as Associated Editor of IEEE Access and IET Biometrics. He is a member of the EAB, IAPR, and IEEE.
Dr. Ranjita Das is currently serving as Head and Assistant Professor, Department of Computer Science and Engineering, National Institute of Technology Mizoram. She has joined the National Institute of Technology Mizoram in the year 2011. She did her PhD. from NIT Mizoram, M. Tech from Tezpur University, and B. Tech. from NIT Agartala. She has over 10 years of teaching experience. Her research was in the areas of pattern recognition, information retrieval, computational biology, and machine learning. She has published 20 journal and international conference papers in various journals with SCI impact factors, SCOPUS index, and also in conference proceedings of Springer, IEEE, etc. She has two ongoing sponsored projects funded by DBT and SERB. Under her supervision, presently ten research scholars are doing research work. She was recipient of best paper awards in the conferences IEEE-INDICON-2017, ICACCP-2019, IC4E-2020.
Bibliographic Information
Book Title: Evolution in Computational Intelligence
Book Subtitle: Proceedings of the 9th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA 2021)
Editors: Vikrant Bhateja, Jinshan Tang, Suresh Chandra Satapathy, Peter Peer, Ranjita Das
Series Title: Smart Innovation, Systems and Technologies
DOI: https://doi.org/10.1007/978-981-16-6616-2
Publisher: Springer Singapore
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022
Hardcover ISBN: 978-981-16-6615-5Published: 24 April 2022
Softcover ISBN: 978-981-16-6618-6Published: 25 April 2023
eBook ISBN: 978-981-16-6616-2Published: 23 April 2022
Series ISSN: 2190-3018
Series E-ISSN: 2190-3026
Edition Number: 1
Number of Pages: XVIII, 563
Number of Illustrations: 102 b/w illustrations, 198 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Mobile and Network Security, Signal, Image and Speech Processing