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» Ranked representation of vector fields
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141
Voted
VMV
2000
157views Visualization» more  VMV 2000»
15 years 4 months ago
Visualization of Principal Curvature Directions by Anisotropic Diffusion
Anisotropic diffusion is known to be a powerful tool in image processing. It enables the smoothing of initially noisy images while still retaining, respectively sharpening edges a...
Udo Diewald, Martin Rumpf
150
Voted
TIP
2002
134views more  TIP 2002»
15 years 3 months ago
Curvature of n-dimensional space curves in grey-value images
Local curvature represents an important shape parameter of space curves which are well described by differential geometry. We have developed an estimator for local curvature of spa...
Bernd Rieger, Lucas J. van Vliet
138
Voted
TVCG
2002
99views more  TVCG 2002»
15 years 3 months ago
Lagrangian-Eulerian Advection of Noise and Dye Textures for Unsteady Flow Visualization
A new hybrid scheme (LEA) that combines the advantages of Eulerian and Lagrangian frameworks is applied to the visualization of dense representations of time-dependent vector field...
Bruno Jobard, Gordon Erlebacher, M. Yousuff Hussai...
165
Voted
SIAMREV
2010
174views more  SIAMREV 2010»
14 years 10 months ago
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
The affine rank minimization problem consists of finding a matrix of minimum rank that satisfies a given system of linear equality constraints. Such problems have appeared in the ...
Benjamin Recht, Maryam Fazel, Pablo A. Parrilo
DCC
2006
IEEE
16 years 3 months ago
Compression and Machine Learning: A New Perspective on Feature Space Vectors
The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
D. Sculley, Carla E. Brodley