基于支持向量机的多光谱图像地质单元分类

M. Kovačević, B. Bajat, B. Trivic, R. Pavlovic
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引用次数: 30

摘要

地质调查空间定量预测与分类技术正在迅速发展。最近机器学习技术的应用证实了它们在这一研究领域应用的可能性。本文介绍了基于Landsat多光谱影像源的地质单元分类中,基于统计学习理论的最新成果——支持向量机方法。初步的实验表明了所提出的分类方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Geological Units Classification of Multispectral Images by Using Support Vector Machines
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.
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