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Verlag: New York/ NY, Springer US., 2006
ISBN 10: 0387444343 ISBN 13: 9780387444345
Sprache: Englisch
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In den Warenkorb2006. 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.
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In den WarenkorbZustand: New. pp. 208 69 Illus.
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In den WarenkorbGebunden. Zustand: 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. .
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Verlag: Springer-Verlag New York Inc., 2010
ISBN 10: 1441942718 ISBN 13: 9781441942715
Sprache: Englisch
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In den WarenkorbZustand: New. Series: Environmental and Ecological Statistics. Num Pages: 190 pages, 69 black & white illustrations, biography. BIC Classification: RGV. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 11. Weight in Grams: 326. . 2010. 1st ed. Softcover of orig. ed. 2006. Paperback. . . . .
Verlag: Springer-Verlag New York Inc., 2006
ISBN 10: 0387444343 ISBN 13: 9780387444345
Sprache: Englisch
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In den WarenkorbZustand: New. Describes an integrated approach to using remotely sensed data in conjunction with geographic information systems for landscape analysis. This work compresses remotely sensed data into an analytical image-map that is compatible with the geographic information systems as well as freeware viewers. Series: Environmental and Ecological Statistics. Num Pages: 190 pages, 69 black & white illustrations, biography. BIC Classification: RGV. Category: (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 12. Weight in Grams: 1040. . 2006. Hardback. . . . .
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In den WarenkorbPaperback. Zustand: Brand New. 190 pages. 9.00x6.00x0.47 inches. In Stock.
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In den WarenkorbBuch. 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.
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In den WarenkorbZustand: New.
Verlag: Springer-Verlag New York Inc., New York, NY, 2010
ISBN 10: 1441942718 ISBN 13: 9781441942715
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: new. Paperback. 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. 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. We refer to the segregated scene segments as patterns, since they provide a basis for perception of pattern. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Verlag: Springer-Verlag New York Inc., New York, NY, 2006
ISBN 10: 0387444343 ISBN 13: 9780387444345
Sprache: Englisch
Anbieter: Grand Eagle Retail, Mason, OH, USA
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In den WarenkorbHardcover. Zustand: new. Hardcover. 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. 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. We refer to the segregated scene segments as patterns, since they provide a basis for perception of pattern. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Verlag: Springer-Verlag New York Inc., 2010
ISBN 10: 1441942718 ISBN 13: 9781441942715
Sprache: Englisch
Anbieter: Kennys Bookstore, Olney, MD, USA
EUR 181,21
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In den WarenkorbZustand: New. Series: Environmental and Ecological Statistics. Num Pages: 190 pages, 69 black & white illustrations, biography. BIC Classification: RGV. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 11. Weight in Grams: 326. . 2010. 1st ed. Softcover of orig. ed. 2006. Paperback. . . . . Books ship from the US and Ireland.