Stereology and Stochastic Geometry: Computational Imaging and Vision, cartea 28
Autor John E. Hilliard, L.R. Lawsonen Limba Engleză Paperback – 9 oct 2011
Din seria Computational Imaging and Vision
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Specificații
ISBN-13: 9789048164554
ISBN-10: 9048164559
Pagini: 512
Ilustrații: XVII, 488 p. 42 illus.
Dimensiuni: 155 x 235 x 27 mm
Ediția:Softcover reprint of the original 1st ed. 2003
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Computational Imaging and Vision
Locul publicării:Dordrecht, Netherlands
ISBN-10: 9048164559
Pagini: 512
Ilustrații: XVII, 488 p. 42 illus.
Dimensiuni: 155 x 235 x 27 mm
Ediția:Softcover reprint of the original 1st ed. 2003
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Computational Imaging and Vision
Locul publicării:Dordrecht, Netherlands
Public țintă
ResearchCuprins
1 Images and Patterns.- 2 Mathematical Preliminaries.- 3 Definitions, Sets and Measures.- 4 Random Probes.- 5 General Shape-independent Relationships.- 6 Shape-dependent Intercept Distributions.- 7 Relationships for Projected Images.- 8 Stereological Sampling and Statistics.- 9 Multidimensional Generalizations.- 10 Topics in Stochastic Geometry.- Appendix: Additional Topics in Analysis.- A.1 Systems of Numbers.- A.2 Additional Material on Sets.- A.3 Topics Concerning Measure.- A.4 Bibliography.
Recenzii
From the reviews:
"Mathematical stereology aims to make inference about the properties of random sets in Euclidean space using numerical characteristics of their lower-dimensional sections or projections. The main tools are based on application of methods from stochastic geometry (in particular point processes), convex geometry and geometric measure theory. … The book under review aims to provide an introduction to stereology for non-mathematicians." (Ilya S. Molchanov, Zentralblatt MATH, Vol. 1108 (10), 2007)
"Mathematical stereology aims to make inference about the properties of random sets in Euclidean space using numerical characteristics of their lower-dimensional sections or projections. The main tools are based on application of methods from stochastic geometry (in particular point processes), convex geometry and geometric measure theory. … The book under review aims to provide an introduction to stereology for non-mathematicians." (Ilya S. Molchanov, Zentralblatt MATH, Vol. 1108 (10), 2007)