Intelligent Big Multimedia Databases (eBook)

by (Author)

  • 62,726 Words
  • 324 Pages

Multimedia databases address a growing number of commercially important applications such as media on demand, surveillance systems and medical systems. The book presents essential and relevant techniques and algorithms to develop and implement large multimedia database systems.

The traditional relational database model is based on a relational algebra that is an offshoot of first-order logic and of the algebra of sets. The simple relational model is not powerful enough to address multimedia data. Because of this, multimedia databases are categorized into many major areas. Each of these areas are now so extensive that a major understanding of the mathematical core concepts requires the study of different fields such as information retrieval, digital image processing, feature extraction, fractals, machine learning, neuronal networks and high-dimensional indexing. This book unifies the essential concepts and recent algorithms into a single comprehensive volume.

Contents:
  • Introduction
  • Multimedia Databases
  • Transform Functions
  • Compression
  • Feature Extraction
  • Low Dimensional Indexing
  • Approximative Indexing
  • High Dimensional Indexing
  • Dealing with Text Databases
  • Statistical Supervised Machine Learning
  • Multimodal Fusion
  • Software Architecture
  • Multimedia Databases in Medicine

Readership: Professionals, academics, researchers and graduate students in databases, artificial intelligence, pattern recognition and neural networks.

Multimedia databases address a growing number of commercially important applications such as media on demand, surveillance systems and medical systems. The book presents essential and relevant techniques and algorithms to develop and implement large multimedia database systems.

The traditional relational database model is based on a relational algebra that is an offshoot of first-order logic and of the algebra of sets. The simple relational model is not powerful enough to address multimedia data. Because of this, multimedia databases are categorized into many major areas. Each of these areas are now so extensive that a major understanding of the mathematical core concepts requires the study of different fields such as information retrieval, digital image processing, feature extraction, fractals, machine learning, neuronal networks and high-dimensional indexing. This book unifies the essential concepts and recent algorithms into a single comprehensive volume.

Contents:
  • Introduction
  • Multimedia Databases
  • Transform Functions
  • Compression
  • Feature Extraction
  • Low Dimensional Indexing
  • Approximative Indexing
  • High Dimensional Indexing
  • Dealing with Text Databases
  • Statistical Supervised Machine Learning
  • Multimodal Fusion
  • Software Architecture
  • Multimedia Databases in Medicine

Readership: Professionals, academics, researchers and graduate students in databases, artificial intelligence, pattern recognition and neural networks.


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