Many industrial manufacturing processes depend on the rapid and accurate measurement of circular objects, for example, pipe, tube and ball and roller bearings, to ensure that the c...
A generative probabilistic model for objects in images is presented. An object consists of a constellation of features. Feature appearance and pose are modeled probabilistically. ...
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
Coreference analysis, also known as record linkage or identity uncertainty, is a difficult and important problem in natural language processing, databases, citation matching and ...
A constraint satisfaction problem (CSP) is a problem to find an assignment that satisfies given constraints. An interesting approach to CSP is a repair-based method that first gen...