We present in this paper different principles to induce belief functions from probabilities. Hence, we decide to use these functions in a pattern recognition ...
Abstract – In a lot of operational situations, we have to deal with uncertain and inaccurate information. The theory of belief functions is a mathematical ...
We present in this paper different principles to induce belief functions from probabilities. Hence, we decide to use these functions in a pattern recognition ...
We present in this paper different principles to induce belief functions from probabilities. Hence, we decide to use these functions in a pattern recognition ...
Different principles to induce belief functions from probabilities are presented, which will be applied to seabed characterization in a pattern recognition ...
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Pierre-Emmanuel Doré, Anthony Fiche, Arnaud Martin. Models of belief functions—Impacts for patterns recognitions. Information Fusion, 2010, Edinburgh, ...
Belief functions are used for pattern recognition, multi -sensor data fusion, diagnosis... A nice property of belief functions is that only what is known is ...
Recognizing patterns allows us to predict and expect what is coming. The process of pattern recognition involves matching the information received with the ...
Furthermore, the belief functions framework is considered to represent the uncertainty and imprecision about the class of a new sample where the focal elements ...
[PDF] On Conditional Belief Functions in Directed Graphical Models in the ...
pshenoy.ku.edu › Papers
Jun 10, 2023 · Abstract. The primary goal is to define conditional belief functions in the Dempster-Shafer theory. We do so similarly to probability ...