计算机应用研究2017，Vol.34Issue(2)：621-625,5.DOI:10.3969/j.issn.1001-3695.2017.02.066
基于深度特征与非线性降维的图像数据集可视化方法
Image dataset visualization method based on deep features and nonlinear dimension reduction
李阳 1张亚非 1徐玉龙 1王家宝 1苗壮1
作者信息
- 1. 解放军理工大学指挥信息系统学院,南京210007
- 折叠
摘要
Abstract
In order to reduce the loss of dimension reduction in high dimensional image dataset and improve the effect of data visualization,this paper proposed a new image dataset visualization method based on the combination of deep features and nonlinear dimension reduction.This method firstly designed and trained a convolutional neural network model,and the single model on the MNIST dataset achieved the highest recognition accuracy.Secondly,it used the high precision model to extract the deep middle layer features as an effective representation of the image dataset.Finally,it used nonlinear dimension reduction method to reduce the features into two-dimensional and realized data visualization.Experimental results show that this method can effectively avoid the loss of traditional dimension reduction in image dataset visualization,and the visualization result is very obviouLS.关键词
数据可视化/深度学习/非线性降维/卷积神经网络Key words
data visualization/deep learning/nonlinear dimension reduction/CNN分类
信息技术与安全科学引用本文复制引用
李阳,张亚非,徐玉龙,王家宝,苗壮..基于深度特征与非线性降维的图像数据集可视化方法[J].计算机应用研究,2017,34(2):621-625,5.
