• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Computational intelligence for knowledge-based systems design >Using Uncertainty Information to Combine Soft Classifications
【24h】

Using Uncertainty Information to Combine Soft Classifications

机译：使用不确定性信息组合软分类

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The classification of remote sensing images performed with different classifiers usually produces different results. The aim of this paper is to investigate whether the outputs of different soft classifications may be combined to increase the classification accuracy, using the uncertainty information to choose the best class to assign to each pixel. If there is disagreement between the outputs obtained with the several classifiers, the proposed method selects the class to assign to the pixel choosing the one that presents less uncertainty. The proposed approach was applied to an IKONOS image, which was classified using two supervised soft classifiers, the Multi-layer Perceptron neural network classifier and a fuzzy classifier based on the underlying logic of the Minimum-Distance-to-Means. The overall accuracy of the classification obtained with the combination of both classifications with the proposed methodology was higher than the overall accuracy of the original classifications, which shows that the methodology is promising and may be used to increase classification accuracy. Soft classifiers, uncertainty information, combining soft classifications.
机译：用不同的分类器进行的遥感图像分类通常会产生不同的结果。本文的目的是使用不确定性信息来选择分配给每个像素的最佳类别，以研究是否可以合并不同软分类的输出以提高分类精度。如果使用多个分类器获得的输出之间存在分歧，则所提出的方法选择要分配给像素的类别，并选择不确定性较小的像素。所提出的方法被应用于IKONOS图像，该图像使用两个监督的软分类器，多层感知器神经网络分类器和基于最小距离均值逻辑的模糊分类器进行分类。通过将两种分类与所提出的方法相结合而获得的分类的整体准确性高于原始分类的整体准确性，这表明该方法很有希望，可用于提高分类准确性。软分类器，不确定性信息，组合软分类。

著录项

  • 来源
  • 会议地点 Dortmund(DE);Dortmund(DE)
  • 作者

    Luisa M.S. Gon$alves; Cidalia C. Fonte; Mario Caetano;

  • 作者单位

    Polytechnic Institute of Leiria, School of Technology and Managment,Department of Civil Engeneering, Portugal,Institute for Systems and Computers Engineering at Coimbra, Portugal;

    Institute for Systems and Computers Engineering at Coimbra, Portugal,Department of Mathematics, University of Coimbra, Portugal;

    Portuguese Geographic Institute (IGP), Remote Sensing Unit (RSU), Lisboa, Portugal,CEGI, Instituto Superior de Estatistica e Gestao de Informac.ao, ISEGI,Universidade Nova de Lisboa, 1070-312 Lisboa, Portugal;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 信息处理（信息加工）;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号