Prediction of Visual Perception from BOLD fMRI

被引：0

作者：

Halthor, Ajay ^{[1
]}

Kumar, Anil K. M. ^{[1
]}

机构：

[1] SJCE, Dept Comp Sci, Mysore, Karnataka, India

来源：

2017 2ND INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS, COMPUTING AND IT APPLICATIONS (CSCITA) | 2017年

关键词：

Visual Perception; Object Recognition; Multi Voxel Pattern Analysis; fMRI Analysis; Brain modeling; Feature Selection; Image Smoothing;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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%.

引用

页码：78 / 83

页数：6

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