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ICCV
2009
IEEE
15 years 26 days ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
ECCV
2008
Springer
14 years 6 months ago
Window Annealing over Square Lattice Markov Random Field
Monte Carlo methods and their subsequent simulated annealing are able to minimize general energy functions. However, the slow convergence of simulated annealing compared with more ...
Ho Yub Jung, Kyoung Mu Lee, Sang Uk Lee
BMVC
2002
13 years 10 months ago
Randomized RANSAC with T(d, d) test
Many computer vision algorithms include a robust estimation step where model parameters are computed from a data set containing a significant proportion of outliers. The RANSAC al...
Jiri Matas, Ondrej Chum
CORR
2010
Springer
186views Education» more  CORR 2010»
13 years 8 months ago
Channel Estimation for Opportunistic Spectrum Access: Uniform and Random Sensing
The knowledge of channel statistics can be very helpful in making sound opportunistic spectrum access decisions. It is therefore desirable to be able to efficiently and accurately...
Quanquan Liang, Mingyan Liu
FPL
2010
Springer
139views Hardware» more  FPL 2010»
13 years 5 months ago
Mapping Multiple Multivariate Gaussian Random Number Generators on an FPGA
A Multivariate Gaussian random number generator (MVGRNG) is an essential block for many hardware designs, including Monte Carlo simulations. These simulations are usually used in a...
Chalermpol Saiprasert, Christos-Savvas Bouganis, G...