An object-oriented optimization system

Author

Cunningham, G.S. ; Hanson, K.M. ; Jennings, G.R., Jr. ; Wolf, D.R.

Author_Institution

Los Alamos Nat. Lab., NM, USA

Volume

3

fYear

1994

fDate

13-16 Nov 1994

Firstpage

826

Abstract

We have described the implementation of a graphical programming tool in the object-oriented language, Smalltalk-80, that allows a user to construct a radiographic measurement model. The measurement model can be used to generate the measurements predicted by a given parameterized model of an experimental object. In this paper, we describe extensions to the graphical programming tool that allow it to be used to perform Bayesian inference on very large sets of object parameters, given real experimental data, by optimizing the likelihood or posterior probability of the parameters, given the real data

Keywords

Bayes methods; Smalltalk; inference mechanisms; maximum likelihood estimation; object-oriented languages; radiography; visual languages; Bayesian inference; MAP estimates; Smalltalk-80; experimental data; experimental object; graphical programming tool; maximum a posteriori estimates; maximum likelihood estimate; object parameters; object-oriented language; object-oriented optimization system; parameterized model; posterior probability; radiographic measurement model; Bayesian methods; Data engineering; Graphics; Laboratories; Maximum likelihood estimation; Object oriented modeling; Object oriented programming; Parameter estimation; Predictive models; Shape measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference

Conference_Location

Austin, TX

Print_ISBN

0-8186-6952-7

Type

conf

DOI

10.1109/ICIP.1994.413773

Filename

413773