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检索条件"机构=Image Processing and Image Communications Key Lab."

共 168 条记录，以下是61-70 订阅

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Detrended cross-correlation analysis of epilepsy electroencephalagram singals

引用

2013 International Conference on Advances in Materials Science and Manufacturing Technology, AMSMT 2013

作者： Zhao, Jun Chang Dou, Wan Hu Ji, Hong Da Wang, Jun Image Processing and Image Communications Key Lab College of Geo and Bio Information Nanjing Univ of Posts and Telecomm Nanjing 210003 China

ISBN: (纸本)9783037857984

The cross-correlation performance between epilepsy electroencephalogram (EEG) signals reflects the status of epilepsy patients which has importance for analyzing long-range correlation of non-stationary signals. For the first time, detrended cross-correlation analysis (DCCA) was applied to analyze different physiological and pathological states of epilepsy EEG signals. It were compared the difference of DCCA values between epilepsy patients' EEG signals and normal subjects' EEG signals. It was found that the DCCA values of epilepsy patients' EEG signals increased compared the normal subjects' EEG signals which can be helpful for medical diagnosis and treatment. © (2013) Trans Tech Publications, Switzerland.

关键词： Electroencephalography

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Appearance model based moving object matching across disjoint camera views

引用

2nd International Conference on Opto-Electronics Engineering and Materials Research, OEMR 2013

作者： Yu, Kong Shuai Hu, Dong Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology The key lab of image processing and image communications of Jiangsu Province Nanjing University of Posts and Telecom Nanjing 210003 China

ISBN: (纸本)9783037857731

A new object tracking scheme for multi-camera surveillance with non-overlapping views is proposed in this paper. Brightness transfer function (BTF) is used to establish relative appearance correspondence between different views. Mixtures of probabilistic principal component analysis (MPPCA) is incooperated to learn the subspace of brightness transfer function with the concern to deal with multiple different brightness areas in a scene. The incremental major color spectrum histogram (IMCSH) is used as similarity measure for reliable matching. Experimental results with real world videos show the effectiveness of the proposed algorithm. © (2013) Trans Tech Publications, Switzerland.

关键词： Luminance

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Fetal electrocardiogram extraction based on modified robust independent component analysis

Fetal electrocardiogram extraction based on modified robust ...

引用

2013 International Conference on Bio-Medical Materials and Engineering, ICBME 2013

作者： Yao, Wen Po Zhao, Jun Chang Zheng, Zheng Zhong Liu, Tie Bing Liu, Hong Xing Wang, Jun Image Processing and Image Communications Key Lab. Nanjing Univ. of Posts and Telecomm Nanjing 210003 China Nanjing General Hospital of Nanjing Military Command Nanjing 210002 China School of Electronic Science and Engineering Nanjing University Nanjing 210093 China

ISBN: (纸本)9783037857557

Fetal electrocardiogram (FECG) separation gets widely attention due to its clinical significance. In the paper, we proposed an improved robust independent component analysis for fetal ECG separation. Firstly, wavelet decomposition was applied to fetal ECG to get the relevant parameters. Then, the RobustICA was used to separate the mixed signals. Compared to robust independent component analysis, computing speed of the improved algorithm increased by an average of 15 percent while minimum mean square error fluctuations 0.0008, which indicated that this algorithm could be effectively used in clinical fetal ECG monitoring. © (2013) Trans Tech Publications, Switzerland.

关键词： Independent component analysis

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Network flow based collective behavior analysis

引用

2013 International Workshop on Behavior and Social Informatics and Computing, BSIC 2013

作者： Hu, Yuting Xie, Rong Zhang, Wenjun Institute of Image Communication and Network Engineering Shanghai Key Lab. of Digital Media Processing and Transmission Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9783319040479

With the large-scale activities increasing gradually, the intelligent video surveillance system becomes more and more popular and important. The trajectory identification and behavior analysis are very important techniques for the intelligent video surveillance system. This paper focuses on the trajectory identification and behavior analysis framework for video surveillance system. The framework is implemented on footbridge video and queuing video of Shanghai World Expo 2010 video surveillance system. The experimental results show the efficiency of our proposed framework. © Springer International Publishing Switzerland 2013.

关键词： Integer programming

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Attention electroencephalogram analysis based on Jensen-Shannon Divergence analysis

Attention electroencephalogram analysis based on Jensen-Shan...

引用

2013 International Conference on Bio-Medical Materials and Engineering, ICBME 2013

作者： Zheng, Zheng Zhong Zhao, Jun Chang Huang, Xiao Lin Wang, Jun Image Processing and Image Communications Key Lab College of Geo and Bio Information Nanjing Univ of Posts and Telecomm Nanjing 210003 China Institute of Biomedical Electronic Engineering School of Electronic Science and Engineering Nanjing University Nanjing 210093 China

ISBN: (纸本)9783037857557

In this paper, the complexity analysis method based on Jensen-Shannon Divergence was used to calculate the complexity of the Idle states, the close eyes states and the count numbers states electroencephalogram. The study found that the JSD value of close eyes states EEG was highest, followed by that of the Idle states EEG, and that of the count numbers states EEG was minimum. The result can be used to assisted clinical diagnosis. © (2013) Trans Tech Publications, Switzerland.

关键词： Electroencephalography

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Epilepsy electroencephalagram singals study based on detrended cross-correlation analysis

Epilepsy electroencephalagram singals study based on detrend...

引用

2013 International Conference on Information,Business and Education Technology(ICIBET 2013)

作者： Junchang Zhao Wanhu Dou Hongda Ji Jun Wang Image Processing and Image Communications Key Lab College of Geo & Bio Information Nanjing Univ of Posts & Telecomm

The cross-correlation performance between epilepsy electroencephalogram (EEG) signals reflects the status of epilepsy patients which has importance for analyzing long-range correlation of non-stationary signals. For the first time, detrended cross-correlation analysis (DCCA) was applied to analyze the α wave of different physiological and pathological states of epilepsy EEG signals. It were compared the difference of DCCA values between epilepsy patients' EEG signals and normal subjects' EEG signals. It was found that the DCCA values of epilepsy patients' EEG signals increased compared the normal subjects' EEG signals which can be helpful for medical diagnosis and treatment.

关键词： least squares linear fitting, detrended cross-correlation analysis, epilepsy, EEG, α wave

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Symbolic transfer entropy analyzed sleep electroencephalogram

Symbolic transfer entropy analyzed sleep electroencephalogra...

引用

2013 International Conference on Information,Business and Education Technology(ICIBET 2013)

作者： Ruijun Chang Liu Yang Qiuping Chen Jun Wang Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm

ISBN: (纸本)9781629932101

The quality of sleep has a great relationship with health. The result of sleep stage classification is an important indicator to measure the quality of sleep. It was found that the symbolic transfer entropy about the α wave of the wake and the first stage of non-rapid eye movement sleep reflect on the changes of sleep stage. And it was confirmed by T test and multisamples experiments. The symbolic transfer entropy can apply into automatic sleep stage classification. By Multi-parameter analysis it could achieve a higher accuracy of sleep stage classification.

关键词： EEG symbolic transfer entropy sleep stage classification, α wave

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Pathological Electrocardiogram Analysis based on Symbolic Relative Entropy

Pathological Electrocardiogram Analysis based on Symbolic Re...

引用

2013 International Conference on Bio-Medical Materials and Engineering(ICBME 2013)

作者： Jiakai Qiu Xiaoliang Huang Suyi Chang Yunxia Wang Jun Wang Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm

In this paper, symbolic relative entropy was used to analyze normal electrocardiogram(ECG), the ECG taken from patient with congestive heart failure(CHF) and Atrial fibrillation(AF) Statistical testing showed that the symbolic relative entropy of normal ECG was distinctly higher than that of CHF while the symbolic relative entropy of CHF was distinctly higher than that of AF It discoved that symbolic relative entropy can be used to analyze the different pathological ECG which could be used to assisted clinical diagnosis

关键词： Symbolic the Relative Entropy Electrocardiogram

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A probability-based object tracking method

A probability-based object tracking method

引用

4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Song, Xu Li, Guoqiang Li, Ying Zhang, Yanning Shaanxi Province Key Lab. of Speech and Image Information Processing Northwestern Polytechnical University Xi'an 710129 China Science and Technology on Electro-optic Control Laboratory Louyang 471009 China

ISBN: (纸本)9783642420566

Here we take advantage of the signal recovery power of Compressive Sensing (CS) to significantly reduce the computational complexity brought by the high-dimension image data, then an effective and efficient low-dimensional subspace representation of the object is computing by applying Principal Component Analysis (PCA) to a collection of object observations which are low-dimensional vectors derived from CS. An incremental PCA algorithm is used to update this subspace model for characterizing the object appearance changes. Meanwhile, two distances derived from Probabilistic Principal Component Analysis (PPCA): distance from feature space (DFFS) and distance in feature space (DIFS), are used to describe visual similarity between the learned subspace representation model and candidate targets. Comparing with the traditional used reconstruction error, the sum of two distances: DFFS + DIFS, is more accurate and more robust to noises and partial occlusions. Numerous experiment demonstrate that subspace representation model can handle the situation that target objects experience pose changes, scale changes, significant illumination variation, partial occlusions and so on. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Compressed sensing

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An improved method in change detection of multitemporal remote sensing image

An improved method in change detection of multitemporal remo...

引用

4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Liao, Fangshun Yu, Sufen Li, Ying Zhang, Yanning Shaanxi Provincial Key Lab. of Speech and Image Information Processing Northwestern Polytechnical University Xi'an Shaanxi 710072 China Science and Technology on Electro-optic Control Laboratory Louyang 471009 China

ISBN: (纸本)9783642420566

Traditional Markov random Field (MRF) methods assume that neighboring pixels tend to have the same lab.l. However, this assumption is always inconsistent with the actual situation and affects the resultant accuracy of the algorithm. To overcome this, we propose an object-based Markov Random Field (OMRF) model and a change detection method based on OMRF model. The OMRF model assumes that pixels within same object are in the same class. First, we generate the difference image from multi-temporal remote sensing images. Second, Mean Shift is applied to extract objects from difference image. Finally, change detection map is generated by iterative algorithm. The experimental results show that the algorithm can effectively improve the detection accuracy of the algorithm on real remote sensing datasets. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Change detection

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