eBook - Supervised and Unsupervised Data Engineering for Multimedia Data
Available Exclusively as an eBook | Part of the AI eBook Collection | Only for Institutional Purchase | Publication Year: 2024
Description
This text presents comprehensive methodologies for processing and analyzing multimedia datasets using both supervised and unsupervised machine learning techniques. It covers feature extraction, classification, clustering, and dimensionality reduction tailored to audio, video, and image data, emphasizing scalable and robust engineering solutions. With applications in pattern recognition, content retrieval, and intelligent media systems, the book serves as a technical reference for researchers and practitioners in data engineering and multimedia analytics.
Table of Contents
1 SLRRT: Sign Language Recognition in Real Time
2 Unsupervised/Supervised Feature Extraction and Feature Selection for Multimedia Data
3 Multimedia Data in Healthcare System
4 Automotive Vehicle Data Security Service in IoT Using ACO Algorithm
5 Unsupervised/Supervised Algorithms for Multimedia Data in Smart Agriculture
6 Secure Medical Image Transmission Using 2-D Tent Cascade Logistic Map
7 Personalized Multi-User-Based Movie and Video Recommender System: A Deep Learning Perspective
8 Sensory Perception of Haptic Rendering in Surgical Simulation
9 Multimedia Data in Modern Education
10 Assessment of Adjusted and Normalized Mutual Information Variants for Band Selection in Hyperspectral Imagery
11 A Python-Based Machine Learning Classification Approach for Healthcare Applications 247
12 Supervised and Unsupervised Learning Techniques for Biometric Systems