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case1339081444.pdf (5.44 MB)
ETD Abstract Container
Abstract Header
Semi-Supervised Visual Texture Based Pattern Classification
Author Info
Hudson, Richard Earl
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=case1339081444
Abstract Details
Year and Degree
2012, Doctor of Philosophy, Case Western Reserve University, EECS - Electrical Engineering.
Abstract
Automated visual classification becomes increasingly practical as cameras and computational power become more accessible. Already, many existing automated visual inspection methods are competitive with human levels of performance. This dissertation presents a semi-supervised visual classification algorithm based on Independent Component Analysis, Yan Karklin’s Hierarchical Bayesian Model algorithm and Bayes’ Theorem. Several problems of current interest, both in industry and the research literature, are used as example applications: mobile robotics, industrial inspection and mammography. Results are given demonstrating the effectiveness of this method.
Committee
Wyatt Newman, PhD (Advisor)
Frank Merat, PhD (Committee Member)
Michael Lewicki, PhD (Committee Member)
Peter Thomas, PhD (Committee Member)
Pages
157 p.
Subject Headings
Electrical Engineering
Keywords
ICA Image Processing
;
Image Segmentation
;
Bayesian Optimal Machine Vision
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Citations
Hudson, R. E. (2012).
Semi-Supervised Visual Texture Based Pattern Classification
[Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1339081444
APA Style (7th edition)
Hudson, Richard.
Semi-Supervised Visual Texture Based Pattern Classification.
2012. Case Western Reserve University, Doctoral dissertation.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=case1339081444.
MLA Style (8th edition)
Hudson, Richard. "Semi-Supervised Visual Texture Based Pattern Classification." Doctoral dissertation, Case Western Reserve University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1339081444
Chicago Manual of Style (17th edition)
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Document number:
case1339081444
Download Count:
772
Copyright Info
© 2012, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.