Supervised and Unsupervised Data Engineering for Multimedia Data

✍ Scribed by Suman Kumar Swarnkar & J P Patra & Sapna Singh Kshatri & Yogesh Kumar Rathore & Tien Anh Tran

• Publisher: WILEY
• Year: 2024
• Tongue: English
• Leaves: 541
• Category: Library

✦ Synopsis

Supervised and Unsupervised Data Engineering for Multimedia Data presents a groundbreaking exploration into the intricacies of handling multimedia data through the lenses of both supervised and unsupervised data engineering. Authored by a team of accomplished experts in the field, this comprehensive volume serves as a go-to resource for data scientists, computer scientists, and researchers seeking a profound understanding of cutting-edge methodologies.

✦ Table of Contents

Table of Contents
Series Page
Title Page
Copyright Page
Dedication
Book Description
List of Figures
List of Tables
Preface
1 SLRRT: Sign Language Recognition in Real Time
1.1 Introduction
1.2 Literature Survey
1.3 Model for Sign Recognition Language
1.4 Experimentation
1.5 Methodology
1.6 Experimentation Results
1.7 Conclusion
Future Scope
References
2 Unsupervised/Supervised Feature Extraction and Feature Selection for Multimedia Data (Feature extraction with feature selection for Image Forgery Detection)
2.1 Introduction
2.2 Problem Definition
2.3 Proposed Methodology
2.4 Experimentation and Results
2.5 Feature Selection & Pre-Trained CNN Models Description
2.6 BAT ELM Optimization Results
Conclusion
Declarations
Consent for Publication
Conflict of Interest
Acknowledgement
References
3 Multimedia Data in Healthcare System
3.1 Introduction
3.2 Recent Trends in Multimedia Marketing
3.3 Challenges in Multimedia
3.4 Opportunities in Multimedia
3.5 Data Visualization in Healthcare
3.6 Machine Learning and its Types
3.7 Health Monitoring and Management System Using Machine Learning Techniques
3.8 Health Monitoring Using K-Prototype Clustering Methods
3.9 AI-Based Robotics in E-Healthcare Applications Based on Multimedia Data
3.10 Future of AI in Health Care
3.11 Emerging Trends in Multimedia Systems
3.12 Discussion
References
4 Automotive Vehicle Data Security Service in IoT Using ACO Algorithm
Introduction
Literature Survey
System Design
Result and Discussion
Conclusion
References
5 Unsupervised/Supervised Algorithms for Multimedia Data in Smart Agriculture
5.1 Introduction
5.2 Background
5.3 Applications of Machine Learning Algorithms in Agriculture
References
6 Secure Medical Image Transmission Using 2-D Tent Cascade Logistic Map
6.1 Introduction
6.2 Medical Image Encryption Using 2D Tent and Logistic Chaotic Function
6.3 Simulation Results and Discussion
6.4 Conclusion
Acknowledgement
References
7 Personalized Multi-User-Based Movie and Video Recommender System: A Deep Learning Perspective
7.1 Introduction
7.2 Literature Survey on Video and Movie Recommender Systems
7.3 Feature-Based Solutions for Movie and Video Recommender Systems
7.4 Fusing: EF – (Early Fusion) and LF – (Late Fusion)
7.5 Experimental Setup
7.6 Conclusions
References
8 Sensory Perception of Haptic Rendering in Surgical Simulation
Introduction
Methodology
Background Related Work
Application
Case Study
Future Scope
Result
Conclusion
Acknowledgement
References
9 Multimedia Data in Modern Education
Introduction to Multimedia
Traditional Learning Approaches
Applications of Multimedia in Education
Conclusion
References
10 Assessment of Adjusted and Normalized Mutual Information Variants for Band Selection in Hyperspectral Imagery
Introduction
Test Datasets
Methodology
Statistical Accuracy Investigations
Results and Discussion
Conclusion
References
11 A Python-Based Machine Learning Classification Approach for Healthcare Applications
Introduction
Methodology
Discussion
References
12 Supervised and Unsupervised Learning Techniques for Biometric Systems
Introduction
Various Biometric Techniques
Major Biometric-Based Problems from a Security Perspective
Supervised Learning Methods for Biometric System
Unsupervised Learning Methods for Biometric System
Conclusion
References
About the Editors
Index
Also of Interest
End User License Agreement