Machine learning techniques for multimedia
Subtitle: case studies on organization and retrieval
By: Matthieu Cord, Pa draig Cunningham (eds.).
Series: Cognitive technologies; Cognitive technologies
Publisher: Springer
Published: 2008
Place of publication: Berlin
Language: eng
Format: [electronic resource] :
Number of pages: 288
ISBN-13: 9783540751717; 9783540751700
Subjects: Multimedia systems; Machine learning
Description: Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations??? the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply. This book provides a comprehensive coverage of the most important machine le.
Notes: Includes bibliographical references and index.

Description based on print version record.
Table of contents: title: Front Matter; Introduction to Bayesian Methods and Decision Theory; Supervised Learning; Unsupervised Learning and Clustering; Dimension Reduction; Online Content-Based Image Retrieval Using Active Learning; Conservative Learning for Object Detectors; Machine Learning Techniques for Face Analysis; Mental Search in Image Databases: Implicit Versus Explicit Content Query; Combining Textual and Visual Information for Semantic Labeling of Images and Videos; Machine Learning for Semi-structured Multimedia Documents: Application to Pornographic Filtering and Thematic Categorization.