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Rule-based data fusion for heterogeneous field sensory system is a challenging research paradigm till date, primarily due to the inherent characteristics in quantifying the output response of the system. The problem gets even critical when we need to deal with a limited number of elemental sensor-units in field, in contrast to traditional theories dealing with denser agglomeration of (identical) sensor...
We attribute the data fusion logistics with dissimilar sensor-cells (taxels) an open-research paradigm, because the in-built characteristics in quantifying the system (output) response is still fuzzy. The problem gets even critical when we are bound to deal with a finite number of elemental taxels, as against traditional theories catering to somewhat denser agglomeration of (identical) sensor units...
Uncertainty makes the analysis of even simple situations difficult. It forces situation analysts to formulate and manage hypotheses during the construction of the explicit representations of the real world situations. Because of human cognitive limitations, this may quickly become overwhelming, even for the most experienced and capable analysts. In an attempt to provide better support systems, this...
The intent of this paper is to show enhancements in level 2 and 3 fusion capabilities through a new class of graph models and solution strategies. The problem today is not often lack of information, but instead, information overload. Graphs have demonstrated to be a useful framework to represent and analyze large amounts of information. Classical strategies such as Bayesian networks, semantic networks...
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