Techniques for inferring a regular language, in the form of a finite automaton, from a sufficiently large sample of accepted and nonaccepted input words, have been employed to cons...
This paper describes a probabilistic multiple-hypothesis framework for tracking highly articulated objects. In this framework, the probability density of the tracker state is repr...
Compressed sensing or compressive sampling (CS) has been receiving a lot of interest as a promising method for signal recovery and sampling. CS problems can be cast as convex prob...
Seung-Jean Kim, Kwangmoo Koh, Michael Lustig, Step...
Many new database application domains such as experimental sciences and medicine are characterized by large sequences as their main form of data. Using approximate representation ...
We model the performance of a speaker recognition system used for surveillance to prioritize a large number of candidate speakers in search of a single target speaker. It is assum...