Approximate inference methods for grid-structured MRFs

Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004. === Includes bibliographical references (p. 43-44). === In this thesis, I compared the mean field, belief propagation, and graph cuts methods for performing approximate infer...

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Bibliographic Details
Main Author: Battocchi, Keith, 1980-
Other Authors: Leslie Kaelbling.
Format: Others
Language:en_US
Published: Massachusetts Institute of Technology 2005
Subjects:
Online Access:http://hdl.handle.net/1721.1/27086
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spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-270862019-05-02T16:15:52Z Approximate inference methods for grid-structured MRFs Approximate inference methods for grid-structured Markov Random Field Battocchi, Keith, 1980- Leslie Kaelbling. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004. Includes bibliographical references (p. 43-44). In this thesis, I compared the mean field, belief propagation, and graph cuts methods for performing approximate inference on an MRF. I developed a method by which the memory requirements for belief propagation could be significantly reduced. I also developed a modification of the graph cuts algorithm that allows it to work on MRFs with very general potential functions. These changes make it possible to use any of the three algorithms on medical imaging problems. The three algorithms were then tested on simulated problems so that their accuracy and efficiency could be compared. by Keith Battocchi. M.Eng.and S.B. 2005-09-06T21:40:17Z 2005-09-06T21:40:17Z 2004 2004 Thesis http://hdl.handle.net/1721.1/27086 56821432 en_US M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 49 p. 1850366 bytes 1853314 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology
collection NDLTD
language en_US
format Others
sources NDLTD
topic Electrical Engineering and Computer Science.
spellingShingle Electrical Engineering and Computer Science.
Battocchi, Keith, 1980-
Approximate inference methods for grid-structured MRFs
description Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004. === Includes bibliographical references (p. 43-44). === In this thesis, I compared the mean field, belief propagation, and graph cuts methods for performing approximate inference on an MRF. I developed a method by which the memory requirements for belief propagation could be significantly reduced. I also developed a modification of the graph cuts algorithm that allows it to work on MRFs with very general potential functions. These changes make it possible to use any of the three algorithms on medical imaging problems. The three algorithms were then tested on simulated problems so that their accuracy and efficiency could be compared. === by Keith Battocchi. === M.Eng.and S.B.
author2 Leslie Kaelbling.
author_facet Leslie Kaelbling.
Battocchi, Keith, 1980-
author Battocchi, Keith, 1980-
author_sort Battocchi, Keith, 1980-
title Approximate inference methods for grid-structured MRFs
title_short Approximate inference methods for grid-structured MRFs
title_full Approximate inference methods for grid-structured MRFs
title_fullStr Approximate inference methods for grid-structured MRFs
title_full_unstemmed Approximate inference methods for grid-structured MRFs
title_sort approximate inference methods for grid-structured mrfs
publisher Massachusetts Institute of Technology
publishDate 2005
url http://hdl.handle.net/1721.1/27086
work_keys_str_mv AT battocchikeith1980 approximateinferencemethodsforgridstructuredmrfs
AT battocchikeith1980 approximateinferencemethodsforgridstructuredmarkovrandomfield
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