Many feature detection algorithms rely on the choice of scale. In this paper, we complement standard scaleselection algorithms with spatial regularization. To this end, we formula...
The goal of this paper is to find sparse and representative spatial priors that can be applied to part-based object localization. Assuming a GMRF prior over part configurations, w...
Identifying repeating structural regularities in circuits allows the minimization of synthesis, optimization, and layout e orts. We introduce in this paper a novel method for ident...
Terms are a concise representation of tree structures. Since they can be naturally defined by an inductive type, they offer data structures in functional programming and mechanis...
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...