We introduce a framework for modeling spatial patterns of shapes formed by multiple objects in an image. Our approach is graph-based where each node denotes an object and attribut...
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
We generalize the classical algorithms of Valiant and Haussler for learning conjunctions and disjunctions of Boolean attributes to the problem of learning these functions over arb...
This paper describes a technology for modelling and rendering heterogeneous objects containing entities of various dimensionalities within a cellular-functional framework based on...
Elena Kartasheva, Valery Adzhiev, Peter Comninos, ...
The objective of this paper is two-fold. The first is to develop a methodology capable of extracting the Human Values Scale (HVS) from the user, with reference to his/her objective...