摘要翻译：
在这一章中，我们给出了两个在信息融合中的应用，以评估在引用{Martin06a}一章中提出的广义比例冲突再分配规则。大多数情况下，组合规则只能在简单的例子中进行计算。本文研究了不同的组合规则，并从实际数据的决策角度对它们进行了比较。实际上，在实际应用中，我们需要一个可靠的决策，而最终的结果才是最重要的。本文介绍了两种应用：一种是对声纳图像中水下沉积物类型的人类专家意见的融合，另一种是对雷达目标识别的分类器融合。
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英文标题：
《Generalized proportional conflict redistribution rule applied to Sonar
  imagery and Radar targets classification》
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作者：
Arnaud Martin (E3I2), Christophe Osswald (E3I2)
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最新提交年份：
2008
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Computer Vision and Pattern Recognition        计算机视觉与模式识别
分类描述：Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.
涵盖图像处理、计算机视觉、模式识别和场景理解。大致包括ACM课程I.2.10、I.4和I.5中的材料。
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一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  In this chapter, we present two applications in information fusion in order to evaluate the generalized proportional conflict redistribution rule presented in the chapter \cite{Martin06a}. Most of the time the combination rules are evaluated only on simple examples. We study here different combination rules and compare them in terms of decision on real data. Indeed, in real applications, we need a reliable decision and it is the final results that matter. Two applications are presented here: a fusion of human experts opinions on the kind of underwater sediments depict on sonar image and a classifier fusion for radar targets recognition.
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PDF链接：
https://arxiv.org/pdf/0806.2008