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An adaptive fuzzy expert system to evaluate human visual performance

机译:评估人类视觉表现的自适应模糊专家系统

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In this work, we present a fuzzy expert system to efficiently evaluate the performance of human observers in a visual detection task. With this system, based on fuzzy logic and the receiver operating characteristic theory, we reduced the duration of visual perception psychophysical experiments, which normally takes too long, to approximately one fourth. We used as input variables the partial performance indexes obtained along each experiment together with the corresponding increments of them. The output variable is the energy of the signal to be detected, which is adjusted adaptively by our system so that the observer reports approximately 80% of correct responses. With shorter adaptive experiments, we eliminate the effects of fatigue and loss of attention that limit considerably the applicability of the related theories and techniques. We also show that our results are equivalent to those obtained through long-lasting traditional psychophysical experiments.
机译:在这项工作中,我们提出了一个模糊专家系统,可以有效地评估视觉检测任务中人类观察者的表现。使用基于模糊逻辑和接收器工作特性理论的该系统,我们将视觉感知心理物理实验的时间(通常耗时太长)减少到大约四分之一。我们将每个实验中获得的部分性能指标及其相应的增量用作输入变量。输出变量是要检测的信号的能量,可以通过我们的系统进行自适应调整,以使观察者报告大约80%的正确响应。通过较短的自适应实验,我们消除了疲劳和注意力分散的影响,这些影响极大地限制了相关理论和技术的适用性。我们还表明,我们的结果与通过长期传统心理物理实验获得的结果相同。

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