A statistical multi-experts approach to image classification and segmentation
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.
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Format: | Thesis |
Language: | eng |
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Massachusetts Institute of Technology
2007
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Online Access: | http://hdl.handle.net/1721.1/38112 |
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author | Mui, Lik |
author2 | Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science |
author_facet | Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science Mui, Lik |
author_sort | Mui, Lik |
collection | MIT |
description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995. |
first_indexed | 2024-09-23T09:27:07Z |
format | Thesis |
id | mit-1721.1/38112 |
institution | Massachusetts Institute of Technology |
language | eng |
last_indexed | 2024-09-23T09:27:07Z |
publishDate | 2007 |
publisher | Massachusetts Institute of Technology |
record_format | dspace |
spelling | mit-1721.1/381122019-04-10T18:27:20Z A statistical multi-experts approach to image classification and segmentation Mui, Lik Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science Electrical Engineering and Computer Science Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995. Includes bibliographical references (leaves 170-177). by Lik Mui. M.Eng. 2007-07-18T13:37:50Z 2007-07-18T13:37:50Z 1995 1995 Thesis http://hdl.handle.net/1721.1/38112 34607627 eng 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 177 leaves application/pdf Massachusetts Institute of Technology |
spellingShingle | Electrical Engineering and Computer Science Mui, Lik A statistical multi-experts approach to image classification and segmentation |
title | A statistical multi-experts approach to image classification and segmentation |
title_full | A statistical multi-experts approach to image classification and segmentation |
title_fullStr | A statistical multi-experts approach to image classification and segmentation |
title_full_unstemmed | A statistical multi-experts approach to image classification and segmentation |
title_short | A statistical multi-experts approach to image classification and segmentation |
title_sort | statistical multi experts approach to image classification and segmentation |
topic | Electrical Engineering and Computer Science |
url | http://hdl.handle.net/1721.1/38112 |
work_keys_str_mv | AT muilik astatisticalmultiexpertsapproachtoimageclassificationandsegmentation AT muilik statisticalmultiexpertsapproachtoimageclassificationandsegmentation |