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dc.contributor.advisorW. Clement Karl.en_US
dc.contributor.authorSaeed, Mohammeden_US
dc.date.accessioned2008-11-07T19:38:06Z
dc.date.available2008-11-07T19:38:06Z
dc.date.copyright1997en_US
dc.date.issued1997en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/43410
dc.descriptionThesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.en_US
dc.descriptionIncludes bibliographical references (leaves 79-82).en_US
dc.description.statementofresponsibilityby Mohammed Saeed.en_US
dc.format.extent82 leavesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Scienceen_US
dc.titleMaximum likelihood parameter estimation of mixture models and its application to image segmentation and restorationen_US
dc.typeThesisen_US
dc.description.degreeM.S.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc37658994en_US


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