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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Subspace Methods for Pattern Recognition in Intelligent Environment

Subspace Methods for Pattern Recognition in Intelligent Environment

Chen, Yen-Wei
C. Jain, Lakhmi

Paperback

Series: Studies in Computational Intelligence, Book 552

Technology & EngineeringGeneral ComputersGeneral Mathematics

ISBN10: 3662501902
ISBN13: 9783662501900
Publisher: Springer Nature
Published: Sep 3 2016
Pages: 199
Weight: 0.68
Height: 0.46 Width: 6.14 Depth: 9.21
Language: English

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.

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