Several recent studies have shown that fluorescent particles can be localized with an accuracy that is well beyond traditional resolution limits. Using a theoretical model of the...
Observing the workload on a computer system during a short (but not too short) time interval may lead to distributions that are significantly different from those that would be o...
A new enhancement of RANSAC, the locally optimized RANSAC (LO-RANSAC), is introduced. It has been observed that, to find an optimal solution (with a given probability), the numbe...
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...
Inspired by tensor voting, we present luminance voting, a novel approach for image registration with global and local luminance alignment. The key to our modeless approach is the ...