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Visual Illusion Induced by Uncertain Environment in Neural Dynamics Cognitive System

机译:神经动力学认知系统不确定环境引起的视觉幻觉

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The visual signal processing mechanism of humans and mammals is precise and complex, better than most current machine vision systems. Visual illusion can show the cognitive functions and mechanisms of the visual system from a unique perspective which are of great significance to the development of computer vision. Firstly, the Gabor filter perfectly simulates the direction and spatial frequency selectivity of the visual cortex cells, thus successfully explaining why the Einstein-Monroe picture has two interpretations when viewing distance is changed and verifying the multi-scale characteristics of the visual neural network. Secondly, by means of nonlinear dynamics, the visual neural dynamics system based on the multi-scale background environment is established to reproduce optical illusions like Herman grid illusion. By understanding the mechanism of visual illusion, it can provide convenient experimental means for realizing the multi-modal information integration of multi-scale neural network and theoretical research of memory fusion model.
机译:人类和哺乳动物的视觉信号处理机制是精确的,复杂,优于大多数电流机视觉系统。视觉幻觉可以从独特的视角显示视觉系统的认知功能和机制,这对计算机视觉的发展具有重要意义。首先,Gabor滤波器完美地模拟了视觉皮质电池的方向和空间频率选择性,从而成功地解释了Einstein-Monroe图片在观看距离时具有两个解释的原因,并验证视觉神经网络的多尺度特征。其次,通过非线性动力学,建立基于多尺度背景环境的视觉神经动力学系统来重现赫尔曼网格错觉等光学幻觉。通过了解视觉幻觉的机制,它可以为实现多尺度神经网络的多模态信息集成和记忆融合模型的理论研究提供方便的实验手段。

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