Abstract. This paper is concerned with the reliable inference of optimal treeapproximations to the dependency structure of an unknown distribution generating data. The traditional ...
Background: The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Oth...
Yvan Saeys, Sven Degroeve, Dirk Aeyels, Pierre Rou...
We address the problem of identifying specific instances of a class (cars) from a set of images all belonging to that class. Although we cannot build a model for any particular in...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
We present a new framework for characterizing and retrieving objects in cluttered scenes. This CBIR system is based on a new representation describing every object taking into acc...
Jaume Amores, Nicu Sebe, Petia Radeva, Theo Gevers...
We propose a novel Bayesian registration formulation in which image location is represented as a latent random variable. Location is marginalized to determine the maximum a priori ...