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» The Computational Complexity of Linear Optics
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PR
2000
106views more  PR 2000»
13 years 7 months ago
Non-linear image processing in hardware
A new ASIC capable of computing rank order "lters, weighted rank order "lters, standard erosion and dilation, soft erosion and dilation, order statistic soft erosion and...
Antonios Gasteratos, Ioannis Andreadis
IJCV
2002
157views more  IJCV 2002»
13 years 7 months ago
Dense Features for Semi-Dense Stereo Correspondence
We present a new feature based algorithm for stereo correspondence. Most of the previous feature based methods match sparse features like edge pixels, producing only sparse dispar...
Olga Veksler
DCG
1998
53views more  DCG 1998»
13 years 7 months ago
Motion Planning in Environments with Low Obstacle Density
We present a simple and e cient paradigm for computing the exact solution of the motionplanning problem in environments with a low obstacle density. Such environments frequently o...
A. Frank van der Stappen, Mark H. Overmars, Mark d...
ML
2002
ACM
143views Machine Learning» more  ML 2002»
13 years 7 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
PC
2002
137views Management» more  PC 2002»
13 years 7 months ago
The Chebyshev iteration revisited
Compared to Krylov space methods based on orthogonal or oblique projection, the Chebyshev iteration does not require inner products and is therefore particularly suited for massiv...
Martin H. Gutknecht, Stefan Röllin