中文版 | English

在结果中检索

CASIA OpenIR
（本次检索基于用户作品认领结果）

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：
Improving Learning Efficiency of Recurrent Neural Network through Adjusting Weights of All Layers in a Biologically-inspired Framework 会议论文
, Anchorage, AK, USA, 2017-5-14
作者:  Huang, Xiao;  Wu, Wei;  Yin, Peijie;  Qiao, Hong
浏览  |  Adobe PDF(466Kb)  |  收藏  |  浏览/下载：232/57  |  提交时间：2020/06/09
Brain-inspired model  emotion  motion learning  recurrent neural network  
Local Discriminant Canonical Correlation Analysis for Supervised PolSAR Image Classification 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2017, 卷号: 14, 期号: 11, 页码: 2102-2106
作者:  Huang, Xiayuan;  Zhang, Bo;  Qiao, Hong;  Nie, Xiangli
浏览  |  Adobe PDF(2283Kb)  |  收藏  |  浏览/下载：349/108  |  提交时间：2017/12/30
Canonical Correlation Analysis (Cca)  Dimensionality Reduction (Dr)  Local Discriminant Embedding (Lde)  Multiview Feature Extraction  Supervised Polarimetric Synthetic Aperture Radar (Polsar) Image Classification  
Distributed asynchronous event-triggered consensus of nonlinear multi-agent systems with disturbances: An extended dissipative approach 期刊论文
NEUROCOMPUTING, 2017, 卷号: 243, 页码: 103-114
作者:  Ma, Chao;  Qiao, Hong
Adobe PDF(1955Kb)  |  收藏  |  浏览/下载：297/57  |  提交时间：2017/07/18
Nonlinear Multi-agent Systems  Extended Dissipative Consensus  Event-triggered Consensus  
SAR target configuration recognition based on the biologically inspired model 期刊论文
NEUROCOMPUTING, 2017, 期号: 234, 页码: 185-191
作者:  Huang, Xiayuan;  Nie, Xiangli;  Wu, Wei;  Qiao, Hong;  Zhang, Bo
浏览  |  Adobe PDF(1628Kb)  |  收藏  |  浏览/下载：377/112  |  提交时间：2017/05/05
Biologically Inspired Model  Sar Target Configuration Recognition  Episodic Features  Semantic Features  Aspect Angle Estimation  
Point correspondence by a new third order graph matching algorithm 期刊论文
PATTERN RECOGNITION, 2017, 卷号: 65, 期号: 0, 页码: 108-118
作者:  Yang, Xu;  Qiao, Hong;  Liu, Zhi-Yong
浏览  |  Adobe PDF(1539Kb)  |  收藏  |  浏览/下载：449/133  |  提交时间：2017/03/09
Graph Matching  Point Correspondence  High Order Constraints  Adjacency Tensor