DocumentCode :
3634497
Title :
Geological Units Classification of Multispectral Images by Using Support Vector Machines
Author :
Miloš 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 :
بازگشت