gebundene Ausgabe. Zustand: Gut. 186 Seiten Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber und kann entsprechende Merkmale aufweisen (Rückenschild, Instituts-Stempel.). In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 495.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 40,49
Anzahl: 4 verfügbar
In den WarenkorbZustand: New. pp. 208 69 Illus.
Sprache: Englisch
Verlag: New York/ NY, Springer US., 2006
ISBN 10: 0387444343 ISBN 13: 9780387444345
Anbieter: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Deutschland
2006. 16 x 24 cm. XVIII, 190 S. XVIII, 190 p. 69 illus. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. (Environmental and Ecological Statistics). Sprache: Englisch.
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 113,55
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Anbieter: moluna, Greven, Deutschland
EUR 124,02
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. Presents a non-conventional approach to multivariate image-structured dataPresents a non-conventional approach to multivariate image-structured dataIncludes supplementary material: sn.pub/extrasDr. Wayne L. Myers earned M.F. .
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - We offer here a non-conventional approach to muhivariate ima- structured data for which the basis is well tested but the analytical ramifi cations are still unfolding. Although we do not formally pursue them, there are several parallels with the nature of neural networks. We employ a systematic set of statistical heuristics for modeling multivariate image data in a quasi-perceptual manner. When the human eye perceives a scene, the elements of the scene are segregated heuristically into compo nents according to similarity and dissimilarity, and then the relationships among the components are interpreted. Similarly, we segregate or seg ment the scene into hierarchically organized components that are subject to subsequent statistical analysis in many modes for interpretive purposes. We refer to the segregated scene segments as patterns, since they provide a basis for perception of pattern. Since they are also hierarchically organ ized, we refer to them further as polypatterns. This leads us to our acro nym of Progressively Segmented Image Modeling As Poly-Patterns (PSIMAPP). Likewise, we formalize our approach in terms of pattern processes and segmentation sequences. In alignment with the terminology of image analysis, we refer to our multivariate measures as being signal bands.