训练人工神经网络在行为反应前对视觉刺激的正确和错误解释进行分类

2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA) Pub Date : 2022-09-14 DOI:10.1109/DCNA56428.2022.9923233

Alexander Kuc, Alisa Batmanova, V. Maksimenko

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引用次数: 0

摘要

我们已经训练了一个人工神经网络(ANN)来预测对不同模糊程度的复杂视觉刺激的正确和错误解释。对于选择的人工神经网络配置，分类准确率为88%。这些结果对新一代辅助技术的发展具有前瞻性。

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Training Artificial Neural Network to Classify Correct and Erroneous Interpretations of Visual Stimuli before Behavioral Response

We have trained an artificial neural network (ANN) to predict correct and erroneous interpretations of complex visual stimuli, Necker cubes with different levels of ambiguity. For the selected configuration of ANN, the classification accuracy was 88%. These results are prospective for developing the new-generation assistive technologies.

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2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)

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