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Parallel learning: a perspective and a framework 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2017, 卷号: 4, 期号: 3, 页码: 389 - 395
作者:  Li Li;  Yilun Lin;  Nanning Zheng;  Fei-Yue Wang
Adobe PDF(1354Kb)  |  收藏  |  浏览/下载:106/21  |  提交时间:2023/03/07
On the Centre of Mass Motion in Human Walking 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 5, 页码: 542-551
作者:  Justin Carpentier;  Mehdi Benallegue;  Jean-Paul Laumond
浏览  |  Adobe PDF(3792Kb)  |  收藏  |  浏览/下载:160/49  |  提交时间:2021/02/23
Human locomotion  analytical model  centre of mass  locomotion signature  synergies.  
Why Deep Neural Nets Cannot Ever Match Biological Intelligence and What To Do About It? 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 5, 页码: 532-541
作者:  Danko Nikolic
浏览  |  Adobe PDF(349Kb)  |  收藏  |  浏览/下载:113/17  |  提交时间:2021/02/23
Artificial intelligence  neural networks  strong artificial intelligence  practopoiesis, machine learning.  
Why and When Can Deep-but Not Shallow-networks Avoid the Curse of Dimensionality: A Review 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 5, 页码: 503-519
作者:  Tomaso Poggio;  Hrushikesh Mhaskar;  Lorenzo Rosasco;  Brando Miranda;  Qianli Liao
浏览  |  Adobe PDF(1711Kb)  |  收藏  |  浏览/下载:190/29  |  提交时间:2021/02/23
Deep learning  fine-grained image classification  semantic segmentation  convolutional neural network (CNN)  recurrent neural network (RNN).  
Event-based Control and Filtering of Networked Systems: A Survey 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 3, 页码: 239-253
作者:  Lei Zou;  Zi-Dong Wang;  Dong-Hua Zhou
浏览  |  Adobe PDF(3631Kb)  |  收藏  |  浏览/下载:170/37  |  提交时间:2021/02/23
Event-triggered transmission  networked systems  event-based control  event-based filtering  event-triggered distributed state estimation  distributed control with event-based protocol.  
PLS-CCA Heterogeneous Features Fusion-based Low-resolution Human Detection Method for Outdoor Video Surveillance 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 2, 页码: 136-146
作者:  Hong-Kai Chen;  Xiao-Guang Zhao;  Shi-Ying Sun;  Min Tan
浏览  |  Adobe PDF(13495Kb)  |  收藏  |  浏览/下载:211/39  |  提交时间:2021/02/23
Low-resolution human detection  partial least squares  canonical correlation analysis  heterogeneous features  outdoor video surveillance.  
A Survey on Deep Learning-based Fine-grained Object Classification and Semantic Segmentation 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 2, 页码: 119-135
作者:  Bo Zhao;  Jiashi Feng;  Xiao Wu;  Shuicheng Yan
浏览  |  Adobe PDF(5409Kb)  |  收藏  |  浏览/下载:175/38  |  提交时间:2021/02/23
Deep learning  fine-grained image classi¯cation  semantic segmentation  convolutional neural network (CNN)  recurrent neural network (RNN).  
Actuator Fault Monitoring and Fault Tolerant Control in Distillation Columns 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 1, 页码: 80-92
作者:  Sulaiman Ayobami Lawal;  Jie Zhang
浏览  |  Adobe PDF(13749Kb)  |  收藏  |  浏览/下载:208/46  |  提交时间:2021/02/23
Dynamic principal component analysis  fault detection and diagnosis  distillation column  fault tolerant controller  inferential control.  
Molecular Dynamics Simulation of Persistent Slip Bands Formation in Nickel-base Superalloys 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 1, 页码: 68-79
作者:  Jian-Feng Huang;  Zhong-Lai Wang;  Er-Fu Yang;  Don McGlinchey;  Yuan-Xin Luo;  Yun Li;  Yi Chen
Adobe PDF(29631Kb)  |  收藏  |  浏览/下载:116/21  |  提交时间:2021/02/23
Persistent slip bands (PSB)  molecular dynamics  superalloys  computational simulation  embedded atom model (EAM).  
An Effective Density Based Approach to Detect Complex Data Clusters Using Notion of Neighborhood Difference 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 1, 页码: 57-67
作者:  S. Nagaraju;  Manish Kashyap;  Mahua Bhattachraya
Adobe PDF(30557Kb)  |  收藏  |  浏览/下载:127/33  |  提交时间:2021/02/23
Density based clustering  neighborhood difference  density-based spatial clustering of applications with noise (DBSCAN)  space density indexing (SDI)  core object.