CSpace

浏览/检索结果: 共5条,第1-5条 帮助

限定条件                
已选(0)清除 条数/页:   排序方式:
Quantitative Analysis of Immunochromatographic Strip Based on Convolutional Neural Network 期刊论文
IEEE ACCESS, 2019, 卷号: 7, 页码: 16257-16263
作者:  Zeng, Nianyin;  Li, Han;  Li, Yurong;  Luo, Xin
Adobe PDF(4383Kb)  |  收藏  |  浏览/下载:167/0  |  提交时间:2019/03/25
Gold immunochromatographic strip  quantitative analysis  image segmentation  CNN  
An inherently nonnegative latent factor model for high-dimensional and sparse matrices from industrial applications 期刊论文
IEEE Transactions on Industrial Informatics, 2018, 卷号: 14, 期号: 5, 页码: 2011-2022
作者:  Luo, Xin;  Zhou, Mengchu;  Li, Shuai;  Shang, Mingsheng
Adobe PDF(805Kb)  |  收藏  |  浏览/下载:416/0  |  提交时间:2019/06/26
Symmetric and Nonnegative Latent Factor Models for Undirected, High-Dimensional, and Sparse Networks in Industrial Applications 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 卷号: 13, 期号: 6, 页码: 3098-3107
作者:  Luo, Xin;  Sun, Jianpei;  Wang, Zidong;  Li, Shuai;  Shang, Mingsheng
Adobe PDF(803Kb)  |  收藏  |  浏览/下载:428/0  |  提交时间:2018/03/05
Big data application  high-dimensional, and sparse (SHiDS) matrix  nonnegative latent factor (NLF) model  symmetry  undirected HiDS network  
Highly Efficient Framework for Predicting Interactions Between Proteins 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 3, 页码: 731-743
作者:  You, Zhu-Hong;  Zhou, MengChu;  Luo, Xin;  Li, Shuai
Adobe PDF(1407Kb)  |  收藏  |  浏览/下载:221/0  |  提交时间:2018/03/15
Big data  feature extraction  kernel extreme learning machine (K-ELM)  low-rank approximation (LRA)  protein-protein interactions (PPIs)  support vector machine (SVM)  
PAPMSC: Power-Aware Performance Management Approach for Virtualized Web Servers via Stochastic Control 期刊论文
JOURNAL OF GRID COMPUTING, 2016, 卷号: 14, 期号: 1, 页码: 171-191
作者:  Shi, Xiaoyu;  Dong, Jin;  Djouadi, Seddik M.;  Feng, Yong;  Ma, Xiao;  Wang, Yefu
Adobe PDF(1140Kb)  |  收藏  |  浏览/下载:114/0  |  提交时间:2018/03/15
Virtualization  Power efficiency  Resource management  Stochastic control  Web application