Books+ Search Results

Subspace Methods for Pattern Recognition in Intelligent Environment

Title
Subspace Methods for Pattern Recognition in Intelligent Environment [electronic resource] / edited by Yen-Wei Chen, Lakhmi C. Jain.
ISBN
9783642548512
Publication
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.
Physical Description
XVI, 199 p. 99 illus., 52 illus. in color : online resource.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This research book provides a comprehensive overview of the state-of-the-art subspace learning methods for pattern recognition in intelligent environment. With the fast development of internet and computer technologies, the amount of available data is rapidly increasing in our daily life. How to extract core information or useful features is an important issue. Subspace methods are widely used for dimension reduction and feature extraction in pattern recognition. They transform a high-dimensional data to a lower-dimensional space (subspace), where most information is retained. The book covers a broad spectrum of subspace methods including linear, nonlinear and multilinear subspace learning methods and applications. The applications include face alignment, face recognition, medical image analysis, remote sensing image classification, traffic sign recognition, image clustering, super resolution, edge detection, multi-view facial image synthesis.
Variant and related titles
Springer ebooks.
Other formats
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
May 07, 2014
Series
Studies in computational intelligence ; 552.
Studies in Computational Intelligence, 552
Contents
Active Shape Model and Its Application to Face Alignment
Condition Relaxation in Conditional Statistical Shape Models
 Independent Component Analysis and Its Application to Classification of High-Resolution Remote Sensing Images
Subspace Construction from Artificially Generated Images for Traffic Sign Recognition
Local Structure Preserving based Subspace Analysis Methods and Applications
Sparse Representation for Image Super-Resolution
Sampling and Recovery of Continuously-Defined Sparse Signals and Its Applications
Tensor-Based Subspace Learning for Multi-Pose Face Synthesis.
Also listed under
C. Jain, Lakhmi.
SpringerLink (Online service)
Citation

Available from:

Online
Loading holdings.
Unable to load. Retry?
Loading holdings...
Unable to load. Retry?