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浏览/检索结果: 共5条，第1-5条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择发表日期升序发表日期降序作者升序作者降序提交时间升序提交时间降序题名升序题名降序 SALIENCY DETECTION VIA LOCAL SINGLE GAUSSIAN MODEL 会议论文 2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2017-01-01 作者:  Xu, Nan;  Guo, Yanqing;  Kong, Xiangwei 收藏  |  浏览/下载：1/0  |  提交时间：2019/12/03 Bottom-up model  local single Gaussian model  saliency map   Efficient Moving Object Segmentation Algorithm Based on the Improvement of Generalized Geodesic Active Contour Model 会议论文 作者:  Chen, Ying;  Yu, Qi 收藏  |  浏览/下载：6/0  |  提交时间：2019/12/02 moving object segmentation  generalized geodesic active contour model  level set function  single gaussian model   Image database retrieval using GMM-AIB framework 期刊论文 Journal of Computational Information Systems, 2012, 卷号: 8, 期号: 22, 页码: 9141-9149 作者:  Li, Junyi;  Li, Jianhua;  Yan, Shuicheng;  Wang, Gang 收藏  |  浏览/下载：2/0  |  提交时间：2019/12/23 AIB clustering  Ensemble learning  Gaussian mixed model  Image representation  Multi-instance learning  Scene recognition  Single-instance bag   The random electrode selection ensemble for EEG signal classification 期刊论文 2010, 2010 Sun, Shiliang; Zhang, Changshui; Lu, Yue 收藏  |  浏览/下载：2/0 An information theoretic approach to model reduction based on frequency-domain Cross-Gramian information (EI CONFERENCE) 会议论文 2010 8th World Congress on Intelligent Control and Automation, WCICA 2010, July 7, 2010 - July 9, 2010, Jinan, China Fu J.; Zhong C.; Ding Y.; Zhou J. 收藏  |  浏览/下载：23/0  |  提交时间：2013/03/25 We focused our attention on model reduction for linear time invariant (LTI) continuous time systems with single input and single output (SISO). We analyzed the strongpoint and shortcoming of an information theoretic approach called minimum information loss method for model reduction. We explained relationships between the steady-state information entropy and controllability information for the Gaussian systems. The controllability  observability and Cross-Gramian information were analyzed in the time-domain. The frequency-domain Cross-Gramian information (FCGI) was defined based on Cross-Gramian matrix containing information associated with both controllability and observability. Furthermore  a valuable application of the frequency-domain Cross-Gramian information to model reduction (FCGMIL) was developed by using the concept and properties of frequency-domain Cross-Gramian information. The performance index of FCGMIL is to minimize the frequency-domain Cross-Gramian information loss caused by eliminating the state variables with weak contributions to Cross-Gramian information over some frequency band. Two numerical examples are illustrated to verify the efficiency of FCGMIL. 2010 IEEE.