This book explains different applications of supervised and unsupervised data engineering for working with multimedia objects. Throughout this book, the contributors highlight the use of Artificial Intelligence-based soft computing and machine techniques in the field of medical diagnosis, biometrics, networking, automation in vehicle manufacturing, data science and automation in electronics industries.
The book presents seven chapters which present use-cases for AI engineering that can be applied in many fields. The book concludes with a final chapter that summarizes emerging AI trends in intelligent and interactive multimedia systems.
The book presents seven chapters which present use-cases for AI engineering that can be applied in many fields. The book concludes with a final chapter that summarizes emerging AI trends in intelligent and interactive multimedia systems.
Key features:
- A concise yet diverse range of AI applications for multimedia data engineering
- Covers both supervised and unsupervised machine learning techniques
- Summarizes emerging AI trends in data engineering
- Simple structured chapters for quick reference and easy understanding
- References for advanced readers
Table of Contents
Chapter 1 a Quantum-Assisted Diagnostics Method for Intelligent- Manufacturing
- Vishal Sharma
- Introduction
- Methodology
- Feature Selection
- Results
- Conclusion
- References
- Measuring Cognitive Workload
- R. K. Kapila Vani and Jayashree Padmanabhan
- Introduction
- Cognitive Workload
- Definition and Applications
- Task Models
- Cognitive Task Model
- Operational Task Model
- Machine Learning
- Traditional Machine Learning Techniques to Detect Cognitive Workload
- Datasets
- Eeglearn
- Eegmat
- Hybrid Eeg-Nirs
- Wm-Eeg
- Stew
- Data Preprocessing
- Feature Extraction
- Time Domain
- Frequency Domain
- Spatial Domain
- Linear Domain
- Nonlinear Dynamics
- Functional Connectivity Features
- Feature Selection
- Filtering Methods
- Wrapper Techniques
- Embedded Techniques
- Ensemble Feature Selection Techniques
- Optimization Techniques
- Classification
- Deep Learning Models
- Performance Evaluation
- Conclusion
- References
- Computing
- C. A. Harikrishnan
- Introduction
- Definition of Cloud Computing
- Characteristics of Cloud Computing
- Types of Cloud
- Public Cloud
- Private Cloud
- Hybrid Cloud
- Services Provided by Cloud Computing
- Platform as a Service
- Infrastructure as a Service
- Software as a Service
- Types of Computing Techniques
- Cluster Computing
- Distributed Computing
- Invasive Sensors
- Grid Computing
- Utility Computing
- Latest Initiatives of Cloud Computing by Various
- Companies/Organizations
- Amazon Web Services
- Microsoft Azure
- Google Apps
- Need for Cloud Computing in Libraries
- Cloud Computing Services and Its Applications in the Library
- Library Automation
- Digital Library and Repository
- Website Hosting
- Searching Scholarly Content
- Storage and Retrieval of Information
- Cloud Computing Platforms in Library and Information Science
- Field
- Duracloud by Duraspace
- Webscale by Oclc
- Ex-Libris Cloud
- Oss Labs
- Enhancing Various Services Provided by the Libraries And
- Information Centres Using Cloud Computing
- E-Learning
- File/Document Sharing
- Interaction With the Users
- Collection Development
- Information Search and Discovery
- Lending of E-Books
- Shared Catalogue/Union Catalogue/Opac
- Document Download and Delivery Service
- Current Awareness Service and Information Literacy/Orientation
- Role of Librarian in the Cloud Environment
- Advantages of Cloud Computing in Library Services
- Cloud Opac
- Less Cost Involved
- Scalability
- Accessibility
- Higher Level Security
- Portability
- Reduced Risk Rate
- Adjustable Storage
- Conclusion
- References
- System: a Bibliometric
- Richard Essah, Darpan Anand, Surender Singh and Isaac Atta Senior Ampofo
- Introduction
- Literature Review
- Review Methodology
- Results and Discussion
- Publications by Year
- Keyword Analysis
- Geographical Analysis of Publications
- Publications Analysis by Organization
- Analysis of Citations
- Analysis by Author
- Analysis of Research Opportunities
- Discussion
- Conclusion
- References
- Algorithms
- Eram Fatima, Ankit Kumar and Anil Kumar Singh
- Introduction
- Proposed Methodology
- Viola Jones
- Deep Reinforcement
- Convolutional Neural Network (Cnn)
- Experimental Results
- Conclusion
- References
- Ritesh Diwaker and Deepak Asrani
- Introduction
- Related Work
- Proposed Methodology
- Fft Decomposition of Audio Signal
- Qr-Cordic Decomposition
- Watermark Embedding Technique
- Experimental Results
- Conclusion
- References
- Education
- Gausiya Yasmeen, Syed Adnan Afaq, Mohd Faisal and Saman Uzma
- Introduction
- Multimedia
- Multimedia Learning Environment
- E-Learning and Educational Technology
- Innovative Teaching and Learning Methods
- Role of Ict
- Blockchain Technology Impact
- Importance of Big Data
- Advent of Artificial Intelligence(Ai)
- Informatics for Learning
- Steam
- Use of Social Media
- Recent Advancements and Benefits of Multimedia Learning
- Conclusion
- References
- Multimedia Systems
- P. Devisivasankari and R. Vijayakumar
- Introduction
- Role of Dl, Ml in Intelligent and Interactive Multimedia Systems
- Specific Applications of Ai
- Enhance the Naturalness, Scalability, and Customization Of
- Intelligent and Interactive Multimedia Systems
- Future Scopes
- Visual Turing Test
- Recent Developments Made in the Turing Test for Multimedia
- An Explanation of Justification in Multimedia Formats
- Automated Forms of Both Machine and Meta-Learning
- Digital Retinas
- The First Part of the Multimedia Turing Test
- Meta-Learning and Automatic Machine Learning
- Conclusion
- References
- Subject Index
Author
- Suman Kumar Swarnkar
- Sapna Singh Kshatri
- Virendra Kumar Swarnkar
- Tien Anh Tran
