Machine Learning for Multimedia Content Analysis

Machine Learning for Multimedia Content Analysis

Challenges in complexity and variability of multimedia data have led to revolutions in machine learning techniques. Multimedia data, such as digital images, audio streams and motion video programs, exhibit richer structures than simple, isolated data items. A number of pixels in a digital image coll...

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Bibliographic Details
Main Authors: Gong, Yihong (Author), Xu, Wei (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Boston, MA : Springer US, 2007.
Subjects:
Computer science.
Database management.
Information storage and retrieval.
Multimedia information systems.
Artificial intelligence.
Computer graphics.
Application software.
Computer Science.
Multimedia Information Systems.
Artificial Intelligence (incl. Robotics).
Computer Applications.
Information Storage and Retrieval.
Database Management.
Computer Graphics.
Online Access:Full Text via HEAL-Link
Table of Contents:
  • Unsupervised Learning
  • Dimension Reduction
  • Data Clustering Techniques
  • Generative Graphical Models
  • of Graphical Models
  • Markov Chains and Monte Carlo Simulation
  • Markov Random Fields and Gibbs Sampling
  • Hidden Markov Models
  • Inference and Learning for General Graphical Models
  • Discriminative Graphical Models
  • Maximum Entropy Model and Conditional Random Field
  • Max-Margin Classifications.

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