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CASIA OpenIR

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Robust multiple cameras pedestrian detection with multi-view Bayesian network 期刊论文
Pattern Recognition, 2015, 卷号: 48, 期号: 5, 页码: 1760-1772
作者:  Peng PX(彭佩玺);  Tian YH(田永鸿);  Wang YW(王耀威);  Li J(李甲);  Huang TJ(黄铁军)
浏览  |  Adobe PDF(16022Kb)  |  收藏  |  浏览/下载：255/65  |  提交时间：2018/01/08
Pedestrian Detection  Multiple Cameras  Multi-view Model  Bayesian Inference  Height Adaptive Projection  
An object recognition approach based on structural feature for cluttered indoor scene 会议论文
Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, Miami, United States, 2014
作者:  Yuan WB(袁文博);  Cao ZQ(曹志强);  Zhao P(赵鹏);  Tan M(谭民);  Yang YQ(杨月全);  Yuan WB(袁文博)
浏览  |  Adobe PDF(1100Kb)  |  收藏  |  浏览/下载：489/230  |  提交时间：2016/06/27
Indoor Scene  Object Recognition  Visual Sensor Network  Structural Feature  Inference Model  
A proposal of SIRMs dynamically connected fuzzy inference model for plural input fuzzy control 期刊论文
FUZZY SETS AND SYSTEMS, 2002, 卷号: 125, 期号: 1, 页码: 79-92
作者:  Yi, JQ;  Yubazaki, N;  Hirota, K
Adobe PDF(234Kb)  |  收藏  |  浏览/下载：223/73  |  提交时间：2015/11/08
Dynamic Importance Degree  Fuzzy Control  Fuzzy Inference Model  Pendulum  Process Control  Sirm  
Vehicle Detection Based on the AND-OR Graph for Congested Traffic Conditions 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2013, 卷号: 14, 期号: 2, 页码: 984-993
作者:  Li, Ye;  Li, Bo;  Tian, Bin;  Yao, Qingming
收藏  |  浏览/下载：165/0  |  提交时间：2015/08/12
Active Basis Model (Abm)  And-or Graph (Aog)  Bottom-up Inference  Maximally Stable Extremal Region (Mser)  Vehicle Detection  
Accurate and Interpretable Bayesian MARS for Traffic Flow Prediction 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2014, 卷号: 15, 期号: 6, 页码: 2457-2469
作者:  Xu, Yanyan;  Kong, Qing-Jie;  Klette, Reinhard;  Liu, Yuncai
收藏  |  浏览/下载：216/0  |  提交时间：2015/08/12
Bayesian Inference  Interpretable Model  Markov Chain Monte Carlo (Mcmc)  Multivariate Adaptive-regression Splines (Mars)  Spatiotemporal Relationship Analysis  Traffic Flow Prediction