- Introductory chapter
2. Computational Intelligence in Multimedia Processing
3. Multimedia labelling, semantic annotation, and metadata
4. Cloud-Based Multimedia Services and related applications
5. Multimedia computing and management in cloud environment
6. CI Techniques, algorithms and innovative methods for processing multimedia data over the Cloud
7. Novel approaches and techniques for co-processing of Cloud hosted multimedia big data
8. Multidimensional visualization systems of multimedia big data on Clouds
9. Deep learning for multimedia
10. Big data Centric Computational Intelligence systems
11. Big data in Social media
12. Predicative Computational Models for Big Data
13. Computational Modelling and Data Integration
14. Large-scale Recommendation Systems and Social Media Systems
15. Data-Centric Service Modelling for big data services
16. Adaptive forecasting systems and Proactive Analytics in Big data Era
17. Big data infrastructure designs to support Big data Science
18. Computational Intelligence enabling innovative big data applications
As an overwhelming volume of data is being generated rapidly from various sources (e.g., intelligent terminals, multimedia information, cloud services, energy system, bio-engineering and health informatics), the computational intelligence paradigms constitutes a promising role in handling the uncertainty, unpredictability (e.g., data volume, velocity and heterogeneity or variety) and real-world optimization problems. This book proposes the broad overview of CI paradigms that covers: Neural Network (NN), Particle Swarm Optimization (PSO), Evolutionary Algorithm (GA), Fuzzy Set (FS), and Rough Sets (RS) and etc. Furthermore, this book highlights the recent research on some representative techniques to elaborate how data centric system formed a powerful platform for processing of cloud hosted multimedia big data could be analyzed, processed and characterized by CI. The CI paradigms not limited to feature selection, optimization approaches for handling high dimensional data, deep learning architectures, hybrid classification and clustering methods in the context of big data infrastructure designs to support big data science centric systems.
This book also provides a view at how techniques in CI can offer solutions in modelling, relationship pattern recognition, clustering, and other problems particular to the bio-engineering field.
It is written for domain experts and developers, who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of data centric system in the context of multi-media cloud, big data era and its related applications such as smarter health care, homeland security, traffic control, trading analysis and telecom etc. The book is well suited for researchers and PhD exploring the significance of data centric systems in the next paradigm of computing.
- Presents a brief overview of computational intelligence paradigms and its significant role in application domains
- Illustrates the state-of-the-art and recent developments in the new theories and applications of CI approaches
- Makes the readers familiar with computational intelligence concepts and technologies that are successfully used in the implementation of cloud centric multimedia services massive data processing
- Provides new advances in the fields of CI for bio-engineering application
Researchers and PhD who want to understand and explore the application of computational intelligence aspects for design and development of data centric system in the context of multi-media cloud, big data era and its related applications such as smarter health care, homeland security, bio engineering systems, robotics and intelligent assistance etc.
- No. of pages:
- © Academic Press 2018
- 1st August 2018
- Academic Press
- Paperback ISBN:
Michael Sheng is a full Professor and Deputy Head of the School of Computer Science at the University of Adelaide. Michael holds a PhD degree in computer science from the University of New South Wales (UNSW) and has 6-yearexperience as a senior software engineer in industries. Prof Sheng has more than 265 publications as edited books and proceedings, refereed book chapters, and refereed technical papers in leading journals and conferences. He is one of the top-ranked authors in the "World Wide Web" research area by Microsoft Academic Search. Prof Michael Sheng is the recipient of the ARC (Australian Research Council) Future Fellowship (2014), Chris Wallace Award for Outstanding Research Contribution (2012), and Microsoft Research Fellowship (2003).
School of Computer Science, The University of Adelaide, Australia
Quan Z. (Michael) Sheng is currently a full Professor and Head of Department of Computing, at Macquarie University. Prof. Sheng has more than 10 years' research and development experience in the Internet of Things (IoT) and related areas such as service-oriented computing, radio frequency identification (RFID), sensor networks, and big data analytics. He has published more than 280 publications in these areas and is one of the top-ranked authors in the "World Wide Web" research area according to Microsoft Academic Search. Prof. Michael Sheng is the recipient to a number of prestigious awards including ARC Future Fellowship in 2014, Chris Wallace Award for Outstanding Research Contribution (2012), and Microsoft Research Fellowship (2003).
Professor and Head of Department of Computing, Macquarie University, Sydney, Australia
Prof. Zhiyong Zhang received his Master, Ph.D. degrees in Computer Science from Dalian University of Technology and Xidian University, respectively. He was a Post-Doctoral Research Fellow at Xi'an Jiaotong University, China. He is currently a full Henan Province Distinguished Professor and Dean with Department of Computer Science, College of Information Engineering, Henan University of Science & Technology. Prof. Zhang is a visiting professor of Computer Science Department, Iowa State University. He is an ACM Senior Member, IEEE Senior Member, IEEE Systems, Man, Cybernetics Society Technical Committee on Soft Computing, World Federation on Soft Computing Young Researchers Committee, Membership for Digital Rights Management Technical Specialist Workgroup Attached to China National Audio, Video, Multimedia System and Device Standardization Technologies Committee. Prof. Zhang’s research interests include multimedia social networks and digital rights management, applied soft computing, trusted computing, as well as security risk management. He has published over 80 scientific papers and four books on the above research fields, and held 8 granted patents.
Dean, Department of Computer Science, Henan University of Science and Technology, China