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引用次数: 0

摘要

本文挑战了将数据融合问题分层划分为“层次”的做法。JDL数据融合模型及其变体被视为一种划分问题空间的方法,这种方法倾向于支持不同类型的解决方案。这些模型中呈现的融合分层视图是对一个领域的粗略的基于工程的表示,这个领域已经在哲学家和认知科学家几个世纪以来开发的基于分析和经验的模型中得到了解决。这些本体论和认知模型涉及的区别不一定都是等级或顺序的。分层划分——虽然通常在描述融合问题时很方便——不应该成为跨越层次的融合解决方案的障碍。提出了一种更灵活、更全面的分区方案。
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Levels?
This paper challenges the familiar hierarchical partitioning of data fusion problems into "levels". The JDL data fusion model and its variants are seen as a method to partition a problem space in a way that tends to support different types of solutions. The layered view of fusion presented in these models is a rough engineering-based representation of a domain that has been addressed in analytically- and empirically-based models developed over centuries by philosophers and cognitive scientists. These ontological and cognitive models involve distinctions that are not all necessarily hierarchical or sequential. A hierarchical partitioning - while often convenient in characterizing fusion problems - should not be an impediment to fusion solutions that span the levels. A more flexible and comprehensive partitioning scheme is suggested.
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