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Geological Units Classification of Multispectral Images by Using Support Vector Machines
dc.creator | Kovačević, Miloš | |
dc.creator | Bajat, Branislav | |
dc.creator | Trivić, Branislav | |
dc.creator | Pavlović, Radmila | |
dc.date.accessioned | 2019-04-19T14:13:38Z | |
dc.date.available | 2019-04-19T14:13:38Z | |
dc.date.issued | 2009 | |
dc.identifier.uri | https://grafar.grf.bg.ac.rs/handle/123456789/235 | |
dc.description.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. | en |
dc.rights | restrictedAccess | |
dc.source | 2009 International Conference On Intelligent Networking and Collaborative Systems (Incos 2009) | |
dc.subject | image classification | en |
dc.subject | Landsat | en |
dc.subject | multispectral images | en |
dc.subject | support vector machines | en |
dc.title | Geological Units Classification of Multispectral Images by Using Support Vector Machines | en |
dc.type | conferenceObject | |
dc.rights.license | ARR | |
dc.citation.other | : 267- | |
dc.citation.spage | 267 | |
dc.identifier.doi | 10.1109/INCOS.2009.44 | |
dc.identifier.scopus | 2-s2.0-77649308870 | |
dc.identifier.wos | 000289914800047 | |
dc.type.version | publishedVersion |
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