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Fusion of two visual perception systems utilizing cognitive diversity

机译:使用认知多样性的两个视觉感知系统的融合

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Decision-making tasks that are based on perception have been performed routinely by human beings in daily life and decision-makers in daily work. It has been observed that the combination of two perception-based decisions could be better than one, provided that the decision-makers communicate with each other and jointly adopt the most confident judgment; simply select the most confident judgment without any dyadic interaction, or communicate with each other on shareable arguments based on reasoning. In this paper, we report a recently conducted visual perception experiment with decisions from nineteen pairs of subjects and their reported confidence factors when making such a decision. Utilizing the concept of a “cognitive diversity” between two systems and the combinatorial fusion algorithm, our results demonstrated that the fusion of two visual perception decision systems can be better than each of the individual systems only if the two systems perform relatively good and they are cognitively diverse. Our study not only provides a robust algorithm to fuse two visual perception decision-making systems, but also suggests a resilient approach to use the cognitive diversity in fusion when the performance of each individual system is not known or cannot be obtained, which is often the case for complex problems.
机译:基于感知的决策任务已经在日常工作中的日常生活和决策者中经常被人类进行。已经观察到,基于感知的决定的组合可能比其中更好,只要决策者互相沟通并共同采取最有自信的判断;只需在没有任何二元交互的情况下选择最自信的判断,或者根据推理,在可共享的参数上互相通信。在本文中,我们报告了最近进行的视觉感知实验,并在做出如此决定时从十九对象的决定和他们报告的置信因素进行了决定。利用A&#x201c的概念;认知多样性”在两个系统和组合融合算法之间,我们的结果表明,只有当两个系统执行相对较好并且它们是认知的多样化时,两个视觉感知决策系统的融合才能优于每个单独的系统。我们的研究不仅提供了一种熔化的熔断器算法,可以融合两个视觉感知决策系统,而且还表明,当每个单独的系统的性能未知或无法获得时,融合在融合中使用认知多样性的弹性方法,这通常是复杂问题的情况。

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