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140122 ||| eng |
| 020 |
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|a 9780306479304
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| 100 |
1 |
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|a Laxminarayan, Swamy
|e [editor]
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| 245 |
0 |
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|a PDE and Level Sets
|h Elektronische Ressource
|b Algorithmic Approaches to Static and Motion Imagery
|c edited by Swamy Laxminarayan
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| 250 |
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|a 1st ed. 2002
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| 260 |
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|a New York, NY
|b Springer US
|c 2002, 2002
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| 300 |
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|a XXIII, 414 p. 361 illus. in color
|b online resource
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| 505 |
0 |
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|a Basics of PDEs and Level Sets -- Level Set Extentions, Flows and Crack Propagation -- Geometric Regularizers for Level Sets -- Image Segmentation Via PDEs -- Motion Imagery Segmentation Via PDE -- Motion Imagery Segmentation Via PDE -- Medical Image Segmentation Using Level Sets -- Subjective Surfaces -- The Future of PDEs and Level Sets
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| 653 |
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|a Computer graphics
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| 653 |
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|a Computer science
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| 653 |
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|a Neurology
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| 653 |
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|a Computer vision
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| 653 |
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|a Biomedical engineering
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| 653 |
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|a Neurology
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| 653 |
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|a Computer Graphics
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| 653 |
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|a Radiology
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| 653 |
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|a Computer Vision
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| 653 |
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|a Biomedical Engineering and Bioengineering
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| 653 |
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|a Theory of Computation
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b SBA
|a Springer Book Archives -2004
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| 490 |
0 |
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|a Topics in Biomedical Engineering
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| 028 |
5 |
0 |
|a 10.1007/b105356
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| 856 |
4 |
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|u https://doi.org/10.1007/b105356?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 610.28
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| 520 |
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|a PDE & Level Sets: Algorithmic Approaches to Static & Motion Imagery is specially dedicated to the segmentation of complex shapes from the field of imaging sciences using level sets and PDEs. It covers the fundamentals of level sets, different kinds of concepts of both geodesic curvature flows and planar flows, as well as the power of incorporation of regional-statistics in level set framework. In covering this material, this book presents segmentation of object-in-motion imagery based on level sets in eigen analysis framework, while also presenting classical problems of boundary completion in cognitive images, like the pop-up of subjective contours in the famous triangle of Kanizsa using surface evolution framework, or the mean curvature evolution of a graph with respect to the Riemannian metric induced by the image. All results are presented for modal completion of cognitive objects with missing boundaries
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