A study of classification techniques with applications in landmine detection

Author

Akshaya Shankar Puranik

Abstract

"This thesis is on a research problem to identify and classify Gaussian processes. It started with the detection of landmines and moved onto a generalization of the classification problem. The main part of the thesis deals with dimensionality reduction of the large dimension AR spectrums obtained for the landmines. It was demonstrated by earlier research work that many of the algorithms that work well for small dimension feature vectors are unable to duplicate the same classification results for the large dimension vectors. The algorithms for reduction of the feature vector dimension studied here are the Fisher's linear discriminant analysis and the Fisher's multiple discriminant analysis"--Abstract, page iii.

Advisor(s)

Stuller, John A.

Committee Member(s)

Cunningham, David R.
Dagli, Cihan H., 1949-

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Publisher

University of Missouri--Rolla

Publication Date

Spring 2000

Pagination

ix, 60 pages

Note about bibliography

Includes bibliographical references (page 59).

Rights

© 2000 Akshaya Shankar Puranik, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Thesis Number

T 7713

Print OCLC #

43931881

Electronic OCLC #

1101968338

Link to Catalog Record

Electronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.

Recommended Citation

Puranik, Akshaya Shankar, "A study of classification techniques with applications in landmine detection" (2000). Masters Theses. 1898.
https://scholarsmine.mst.edu/masters_theses/1898