Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Deformable models are an attractive approach to recognizing nonrigid objects which have considerable within class variability. However, there are severe search problems associated...
Christopher K. I. Williams, Michael Revow, Geoffre...
In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speciï...
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...