Subspace Methods for Pattern Recognition in Intelligent Environment (Record no. 52362)
[ view plain ]
000 -LEADER | |
---|---|
fixed length control field | 03412nam a22005295i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-642-54851-2 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20200420220229.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 140407s2014 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783642548512 |
-- | 978-3-642-54851-2 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 519 |
245 10 - TITLE STATEMENT | |
Title | Subspace Methods for Pattern Recognition in Intelligent Environment |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | XVI, 199 p. 99 illus., 52 illus. in color. |
490 1# - SERIES STATEMENT | |
Series statement | Studies in Computational Intelligence, |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | 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. |
520 ## - SUMMARY, ETC. | |
Summary, etc | 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. |
700 1# - AUTHOR 2 | |
Author 2 | Chen, Yen-Wei. |
700 1# - AUTHOR 2 | |
Author 2 | C. Jain, Lakhmi. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-642-54851-2 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
264 #1 - | |
-- | Berlin, Heidelberg : |
-- | Springer Berlin Heidelberg : |
-- | Imprint: Springer, |
-- | 2014. |
336 ## - | |
-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
-- | cr |
-- | rdacarrier |
347 ## - | |
-- | text file |
-- | |
-- | rda |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Engineering. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Pattern recognition. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Applied mathematics. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Engineering mathematics. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Engineering. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Appl.Mathematics/Computational Methods of Engineering. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial Intelligence (incl. Robotics). |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Pattern Recognition. |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
-- | 1860-949X ; |
912 ## - | |
-- | ZDB-2-ENG |
No items available.