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Description: 基于图像的时空马尔可夫场在交通流中的应用，东京大学，2005 Spatio-Temporal MRF analyses and its application in traffic flow based images From unversity of Tokyo 2005
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Size: 460855 |
Author: 李鑫 |
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Description: This paper presents a data-oriented tracking framework which aims to recover the spatio-temporal trajectories for an unknown number of interacting objects appearing and disappearing at arbitrary times. Data association is performed at three-levels of a hierarchy: (i) rst, trajectory segments and an associated quality measure are generated by a local analysis of the space-time distribution of observations; (ii) a conservatively constrained association step links nearby consistent segments into intermediate trajectory fragments; and (iii) a last as- sociation step taking into account all available data (observations, trajectory fragments) generates the nal trajectory estimates. The association step relies on the Hungarian algorithm and it also con- siders detection responses below the detection threshold as evidence associated with high ambiguity. We demonstrate the feasibility of the proposed approach applied to the pedestrian tracking task on two challenging datasets.
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Size: 886354 |
Author: kongsuhongbaby@126.com |
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Description: On-Line MCMC Bayesian Model Selection
This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
-On-Line MCMC Bayesian Model Selection
This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar-xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
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Size: 16384 |
Author: 徐剑 |
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Description: 以一维驱动非线性漂移波方程为模型 ,研究了利用外加周期信号成功地对时空混沌进行非反馈控制过程中的相同步.在驱动波坐标系中 ,系统可以被变换成一组在周期势中运动的耦合振子模式,这些模式通过相同步被控制信号逐一控制.研究发现 ,内部模式对外加周期信号的响应方式有2种 一些模式表现出锁频 ,另一些模式则观察到了一种特殊的无锁频的相同步-To drive one-dimensional nonlinear drift wave equation as a model to study the use of periodic signal plus successfully non-spatio-temporal chaos in the process of feedback control phase synchronous. In wave-driven coordinate system, the system can be converted into one group in the periodic potential in movement coupled oscillator model, these models are controlled through the phase synchronous control signal one by one. The study found that the internal model of the external periodic signal increases in response to the way the two kinds of models to show lock, some other mode observed a special kind of without frequency-locking of the phase synchronous
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Size: 186368 |
Author: wang |
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Description: 基于图像的时空马尔可夫场在交通流中的应用，东京大学，2005 Spatio-Temporal MRF analyses and its application in traffic flow based images From unversity of Tokyo 2005-Image-based spatio-temporal Markov field in the traffic flow in the application of the University of Tokyo, 2005 Spatio-Temporal MRF analyses and its application in traffic flow based images From unversity of Tokyo 2005
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Size: 460800 |
Author: 李鑫 |
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Description: The TPRtree 是一种优化的时空访问方法-The TPRtree an optimized spatio-temporal access method
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Size: 2568192 |
Author: 刘国慧 |
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Description: Abstract-In this paper, simple autonomous chaotic circuits
coupled by resistors are investigated. By carrying out computer
calculations and circuit experiments, irregular self-switching phenomenon
of three spatial patterns characterized by the phase
states of quasi-synchronization of chaos can be observed from
only four simple chaotic circuits. This is the same phenomenon
as chaotic wandering of spatial patterns observed very often from
systems with a large number of degrees of freedom. Namely, one
of spatial-temporal chaos observed from systems of large size can
be also generated in the proposed system consisting of only four
chaotic circuits. A six subcircuits case and a coupled chaotic circuits
networks are also studied, and such systems are confirmed
to produce more complicated spatio-temporal phenomena.
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Size: 848896 |
Author: wang |
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Description: 计算机数字图像处理资料，阐述了数字图像处理的各方面知识以及最新进展-It is very important to achieve reliable vehicle
tracking in ITS application such as accident detec-
tion. But the most dicult problem associated with
vehicle tracking is the occlusion e ect among vehicles.
In order to resolve this problem we applied the dedi-
cated algorithm which we de ned as Spatio-Temporal
Markov Random Field model to trac images at an
intersection. Spatio-Temporal MRF considers texture
correlations between consecutive images as well as the
correlation among neighbors within a image. As a re-
sult, we were able to track vehicles at the intersection
robustly against occlusions. Vehicles appear in vari-
ous kinds of shapes and they move in random man-
ners at the intersection. Although occlusions occur in
such complicated manners, the algorithm were able to
segment and track such occluded vehicles at a high
success rate of 93− 96 . The algorithm requires only
gray scale images and does not assume any physical
models of vehicles.
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Size: 10863616 |
Author: christine |
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Description: The impact of narrow angle of arrival at mobile stations on the spatio-temporal
propagation model being considered for the evaluation of multi-antenna systems is
illustrated. It is shown that antenna correlations are sensitive to parameter choices and that
the resulting conclusions may be substantially biased, depending on the propagation model
used
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Size: 71680 |
Author: sim |
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Description: CS理论应用在磁共振成像上。本算法将FOCUSS应用到CS理论上并做了改进，有较好的重建效果。-FOCUSS is originally designed to reconstruct sparse signal. Furthermore, L1 optimization is achieved by successively solving weighted L2 optimization problem, which can be easily implemented. From these advantages, we successfully developed k-t FOCUSS which reconstructs high spatio-temporal resolution of dynamic images such as a heart beating.
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Size: 50500608 |
Author: wangmiaomiao |
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Description: Spatio-temporal BSS by FJTheis
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Size: 14336 |
Author: aahadi |
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Description: Spatio-temporal chaos and localization
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Size: 674816 |
Author: li |
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Description: Spatio-temporal chaos in simple coupled chaotic circuits
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Size: 848896 |
Author: li |
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Description: Spatio-temporal chaos. III. Natural spatio-temporal measures for coupled circle map lattices
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Size: 144384 |
Author: li |
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Description: Visualization of correlation cascade in spatio-temporal chaos using wavelets
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Size: 474112 |
Author: li |
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Description: spatio-temporal Volume Local Phase Quantization (vLPQ)
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Size: 5120 |
Author: joe |
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Description: 分布式时空感知，详细介绍分布式时空感知的实验-Distributed Spatio-Temporal Spectrum Sensing_ An Experimental Study
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Size: 1227776 |
Author: 许靖博 |
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Description: 时空上下文视觉跟踪（STC）算法的解读与代码复现，首次在论文《 Fast Trackingvia Spatio-Temporal Context Learning》提出
-Spatio-Temporal Context Learning visual tracking (STC) algorithm and code reuse existing interpretation, for the first time in the paper《Fast Trackingvia Spatio-Temporal Context Learning》presented
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Size: 553984 |
Author: deng |
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Description: Travel feature mining method based on spatio-temporal trajectory data
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Size: 747520 |
Author: 孙倩 |
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Description: Spiking neuromorphic devices rely on the fact that spikes are an e cient mechanism for
encoding and transmitting spatio-temporal properties of stimuli
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Size: 8028131 |
Author: nitubisen.nuva |
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