Subspace methods pattern recognition (9 Ergebnisse)

Softcover. Zustand: Gut. 198 S. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. Ex-library with stamp and library-signature. GOOD condition, some traces of use. L07711 9783642548505 Sprache: Englisch Gewicht in Gramm: 530.

Zustand: New. In English.

Zustand: New. In English.

Hardcover. Zustand: Brand New. 300 pages. 9.25x6.25x0.75 inches. In Stock.

Taschenbuch. Zustand: Neu. Subspace Methods for Pattern Recognition in Intelligent Environment | Yen-Wei Chen (u. a.) | Taschenbuch | Studies in Computational Intelligence | xvi | Englisch | 2016 | Springer | EAN 9783662501900 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Paperback. Zustand: Brand New. reprint edition. 216 pages. 9.25x6.10x0.46 inches. In Stock.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. …

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

Zustand: Very Good. 187 pp., hardcover, light wear to covers else very good. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. Photos available upon request.…