DocumentCode
3634497
Title
Geological Units Classification of Multispectral Images by Using Support Vector Machines
Author
Milo Kovacevic;Branislav Bajat;Branislav Trivic;Radmila Pavlovic
Author_Institution
Fac. of Civil Eng., Univ. of Belgrade, Belgrade, Serbia
fYear
2009
Firstpage
267
Lastpage
272
Abstract
Quantitative techniques for spatial prediction and classification in geological survey are developing rapidly. The recent applications of machine learning techniques confirm possibilities of their application in this field of research. The paper introduces Support Vector Machines, a method derived from recent achievements in the statistical learning theory, in classification of geological units based on the source of the Landsat multispectral images. The initial experiments suggest the usefulness of the proposed classification approach.
Keywords
"Geology","Multispectral imaging","Support vector machines","Support vector machine classification","Remote sensing","Satellites","Learning systems","Electronic mail","Machine learning","Statistical learning"
Publisher
ieee
Conference_Titel
Intelligent Networking and Collaborative Systems, 2009. INCOS ´09. International Conference on
Print_ISBN
978-1-4244-5165-4
Type
conf
DOI
10.1109/INCOS.2009.44
Filename
5368959
Link To Document