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Subspace Methods For Pattern Recognition In Intelligent Environment
17 Angebote vergleichen
Bester Preis: Fr. 73.78 (€ 75.47)¹ (vom 28.03.2019)Subspace Methods for Pattern Recognition in Intelligent Environment
ISBN: 9783662501900 bzw. 3662501902, in Deutsch, Springer Shop, Taschenbuch, neu.
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. Soft cover.
Subspace Methods for Pattern Recognition in Intelligent Environment
ISBN: 9783642548512 bzw. 3642548512, in Deutsch, Springer Shop, neu, E-Book, elektronischer Download.
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. eBook.
Subspace Methods for Pattern Recognition in Intelligent Environment
ISBN: 9783642548512 bzw. 3642548512, in Englisch, Springer, Berlin/Heidelberg/New York, NY, Deutschland, neu, E-Book, elektronischer Download.
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.
Subspace Methods for Pattern Recognition in Intelligent Environment
ISBN: 9783642548512 bzw. 3642548512, vermutlich in Englisch, Springer Berlin Heidelberg, neu, E-Book, elektronischer Download.
Subspace Methods for Pattern Recognition in Intelligent Environment: 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. Englisch, Ebook.
Subspace Methods For Pattern Recognition In Intelligent Environment
ISBN: 9783662501900 bzw. 3662501902, in Deutsch, Springer Nature, neu.
Yen-Wei Chen, Books, Subspace Methods For Pattern Recognition In Intelligent Environment, 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.
Subspace Methods for Pattern Recognition in Intelligent Environment
ISBN: 9783662501900 bzw. 3662501902, in Englisch, neu.
Subspace Methods for Pattern Recognition in Intelligent Environment, 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.
Subspace Methods for Pattern Recognition in Intelligent Environment (2016)
ISBN: 9783662501900 bzw. 3662501902, in Deutsch, gebundenes Buch, neu, Nachdruck.
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Subspace Methods for Pattern Recognition in Intelligent Environment
ISBN: 9783662501900 bzw. 3662501902, in Deutsch, Springer, Taschenbuch, neu.
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Taal: Engels;ISBN10: 3662501902;ISBN13: 9783662501900; Engelstalig | Paperback.
Subspace Methods for Pattern Recognition in Intelligent Environment (2014)
ISBN: 3662501902 bzw. 9783662501900, in Deutsch, Taschenbuch, neu, Nachdruck.