8 citations · 21 across the 8 of their papers we have counts for
4 papers · 1 filter
The structure of Bayes nets for vision recognition
John Mark Agosta
This paper is part of a study whose goal is to show the effciency of using Bayes networks to carry out model based vision calculations. [Binford et al. 1987] Recognition proceeds b…
Model-based Influence Diagrams for Machine Vision
Tod S. Levitt, John Mark Agosta, Thomas O. Binford
We show an approach to automated control of machine vision systems based on incremental creation and evaluation of a particular family of influence diagrams that represent hypothes…
"Conditional Inter-Causally Independent" Node Distributions, a Property of "Noisy-Or" Models
John Mark Agosta
This paper examines the interdependence generated between two parent nodes with a common instantiated child node, such as two hypotheses sharing common evidence. The relation so ge…
Constraining Influence Diagram Structure by Generative Planning: An Application to the Optimization of Oil Spill Response
John Mark Agosta
This paper works through the optimization of a real world planning problem, with a combination of a generative planning tool and an influence diagram solver. The problem is taken f…