Artificial Intelligence and Multimedia Data Engineering: Volume 1
Description
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.
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
This book is a primary reference for data science and engineering students, researchers and academicians who need a quick and practical understanding of AI supplications in multimedia analysis for undertaking or designing courses. It also serves as a secondary reference for IT and AI engineers and enthusiasts who want to grasp advanced applications of the basic machine learning techniques in everyday applications
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Content
- Cover
- Title
- Copyright
- End User License Agreement
- Contents
- Preface
- List of Contributors
- A Quantum-assisted Diagnostics Method for Intelligent Manufacturing
- Vishal Sharma1,*
- INTRODUCTION
- METHODOLOGY
- Feature Selection
- Results
- CONCLUSION
- REFERENCES
- Evaluation of Bio-inspired Computational Methods for Measuring Cognitive Workload
- R. K. Kapila Vani1,* and Jayashree Padmanabhan2
- 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
- Managing Libraries and Information Centres using Cloud Computing
- Biometric Voting using IoT to Transfer Vote to Centralized System: A Bibliometric
- Richard Essah1,*, Darpan Anand2, Surender Singh3 and Isaac Atta Senior Ampofo4
- 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
- Face Recognition using Convolutional Neural Network Algorithms
- Eram Fatima1,*, Ankit Kumar1 and Anil Kumar Singh1
- INTRODUCTION
- PROPOSED METHODOLOGY
- Viola Jones
- Deep Reinforcement
- Convolutional Neural Network (CNN)
- EXPERIMENTAL RESULTS
- CONCLUSION
- REFERENCES
- Multimedia Security in Audio Signal
- Ritesh Diwaker1,* and Deepak Asrani1
- INTRODUCTION
- RELATED WORK
- PROPOSED METHODOLOGY
- FFT Decomposition of Audio Signal
- QR-Cordic Decomposition
- Watermark Embedding Technique
- EXPERIMENTAL RESULTS
- CONCLUSION
- REFERENCES
- Recent Advancements and Impact of Multimedia in Education
- Gausiya Yasmeen1, Syed Adnan Afaq1,*, Mohd Faisal1 and Saman Uzma2
- 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
- Emerging AI Trends in Intelligent and Interactive Multimedia Systems
- P. Devisivasankari1,* and R. Vijayakumar1
- 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
- Back Cover
