CASIA OpenIR

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:
Building Energy Consumption Prediction: An Extreme Deep Learning Approach 期刊论文
ENERGIES, 2017, 卷号: 10, 期号: 10, 页码: 1-20
作者:  Li, Chengdong;  Ding, Zixiang;  Zhao, Dongbin;  Yi, Jianqiang;  Zhang, Guiqing
浏览  |  Adobe PDF(1918Kb)  |  收藏  |  浏览/下载:318/49  |  提交时间:2017/12/30
Building Energy Consumption  Deep Learning  Stacked Autoencoders  Extreme Learning Machine  
Parameter Identifiability in Statistical Machine Learning: A Review 期刊论文
NEURAL COMPUTATION, 2017, 卷号: 29, 期号: 5, 页码: 1151-1203
作者:  Ran, Zhi-Yong;  Hu, Bao-Gang
浏览  |  Adobe PDF(466Kb)  |  收藏  |  浏览/下载:335/101  |  提交时间:2017/07/18
Parameter Identifiability  Statistical Machine Learning  
Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls 期刊论文
NEUROIMAGE, 2017, 卷号: 145, 页码: 137-165
作者:  Arbabshirani, Mohammad R.;  Plis, Sergey;  Sui, Jing;  Calhoun, Vince D.
Adobe PDF(2676Kb)  |  收藏  |  浏览/下载:465/115  |  提交时间:2017/02/14
Neuroimaging  Machine Learning  Classification  Brain Disorders  Prediction  
Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2016, 卷号: 46, 期号: 10, 页码: 2335-2347
作者:  Qiao, Hong;  Li, Yinlin;  Li, Fengfu;  Xi, Xuanyang;  Wu, Wei
浏览  |  Adobe PDF(2781Kb)  |  收藏  |  浏览/下载:462/153  |  提交时间:2016/06/21
Biologically Inspired  Hierarchical Model  Key Components Learning  Semantic Description  
Enhanced HMAX model with feedforward feature learning for multiclass categorization 期刊论文
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2015, 卷号: 9, 页码: 1-14
作者:  Li, Yinlin;  Wu, Wei;  Zhang, Bo;  Li, Fengfu
浏览  |  Adobe PDF(3664Kb)  |  收藏  |  浏览/下载:378/83  |  提交时间:2016/03/30
Hmax  Biologically Inspired  Feedforward  Saliency Map  Middle Level Patch Learning  Feature Encoding  Multiclass Categorization