Subspace Methods for Pattern Recognition in Intelligent Environment, Kartoniert / Broschiert
Subspace Methods for Pattern Recognition in Intelligent Environment
(soweit verfügbar beim Lieferanten)
- Herausgeber:
- Lakhmi C. Jain, Yen-Wei Chen
- Verlag:
- Springer Berlin Heidelberg, 09/2016
- Einband:
- Kartoniert / Broschiert, Paperback
- Sprache:
- Englisch
- ISBN-13:
- 9783662501900
- Artikelnummer:
- 4483013
- Umfang:
- 216 Seiten
- Ausgabe:
- Softcover reprint of the original 1st edition 2014
- Gewicht:
- 334 g
- Maße:
- 235 x 155 mm
- Stärke:
- 11 mm
- Erscheinungstermin:
- 3.9.2016
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
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Klappentext
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.
