论文标题
使用人工神经网络模拟视觉对象识别中尤里卡效应的反应时间
Simulating reaction time for Eureka effect in visual object recognition using artificial neural network
论文作者
论文摘要
观察一段时间后，人的大脑可以识别隐藏在甚至严重退化的图像中的物体，这被称为尤里卡效应，可能与人类的创造力有关。先前的心理学研究表明，这种“尤里卡识别”的基础是多种随机活动巧合的神经过程。在这里，我们构建了一个基于人造的神经网络模型，该模型模拟了人类尤里卡识别的特征。
The human brain can recognize objects hidden in even severely degraded images after observing them for a while, which is known as a type of Eureka effect, possibly associated with human creativity. A previous psychological study suggests that the basis of this "Eureka recognition" is neural processes of coincidence of multiple stochastic activities. Here we constructed an artificial-neural-network-based model that simulated the characteristics of the human Eureka recognition.
