从BOLD fMRI预测视觉感知

2017 2nd International Conference on Communication Systems, Computing and IT Applications (CSCITA) Pub Date : 2017-04-01 DOI:10.1109/CSCITA.2017.8066528

Ajay Halthor, K. Kumar

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引用次数: 0

摘要

本文的目标是通过分析BOLD功能磁共振成像数据来确定一个人视觉感知的对象。我们使用fMRI数据集并分析单变量和多变量特征选择技术的效果。通过使用主成分分析(PCA)进行降维，使用无核支持向量分类器和适当的平滑进行训练，我们获得了93.16%的准确率:高于目前的92%。

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Prediction of visual perception from BOLD fMRI

The goal of this paper is to determine the object a person visually perceives by analyzing BOLD fMRI data. We use an fMRI dataset and analyze the effects of univariate and multivariate feature selection techniques. By performing dimensionality reduction with Principal Component Analysis (PCA), training with a Support Vector Classifier without a kernel and appropriate smoothing, we obtained a 93.16% accuracy: higher than the state of the art 92%.

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2017 2nd International Conference on Communication Systems, Computing and IT Applications (CSCITA)

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