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第35届中国控制会议

作者： LI Jiang-Wei ZHENG Ding-Fu GUAN Zhi-Hong CHEN Chao-Yang JIANG Xiao-Wei ZHANG Xian-He College of Automation Huazhong University of Science and Technology The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control (Huazhong University of Science and Technology) School of Information and Electrical Engineering Hunan University of Science and Technology College of Mechatronics and Control Engineering Hubei Normal University

ISBN: (纸本)9781509009107

3D mapping for unknown environments is a crucial issue for mobile service robots,which has many important applications in navigation and path *** this paper,we use Microsoft kinect sensor mounted on a mobile robot to obtain3 D *** the process,consistent frames of RGB-D data are captured and *** Closest Point(ICP)algorithm and incremental registration method are employed to perform the fine ***,we use OctoMap to store 3D map of octree representation,an efficient data ***,our results demonstrate the practical applicability and effectiveness of the proposed approach.

关键词： 3D mapping Kinect OctoMap Mobile Robots

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Atorvastatin effect evaluation based on feature combination of three-dimension ultrasound images

Atorvastatin effect evaluation based on feature combination ...

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Medical Imaging 2016: Computer-Aided Diagnosis

作者： Yongkang, Luo Mingyue, Ding Department of Bio-medical Engineering College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei430074 China

ISBN: (纸本)9781510600201

In the past decades, stroke has become the worldwide common cause of death and disability. It is well known that ischemic stroke is mainly caused by carotid atherosclerosis. As an inexpensive, convenient and fast means of detection, ultrasound technology is applied widely in the prevention and treatment of carotid atherosclerosis. Recently, many studies have focused on how to quantitatively evaluate local arterial effects of medicine treatment for carotid diseases. So the evaluation method based on feature combination was proposed to detect potential changes in the carotid arteries after atorvastatin treatment. And the support vector machine (SVM) and 10-fold cross-validation protocol were utilized on a database of 5533 carotid ultrasound images of 38 patients (17 atorvastatin groups and 21 placebo groups) at baseline and after 3 months of the treatment. With combination optimization of many features (including morphological and texture features), the evaluation results of single feature and different combined features were compared. The experimental results showed that the performance of single feature is poor and the best feature combination have good recognition ability, with the accuracy 92.81%, sensitivity 80.95%, specificity 95.52%, positive predictive value 80.47%, negative predictive value 95.65%, Matthew's correlation coefficient 76.27%, and Youden's index 76.48%. And the receiver operating characteristic (ROC) curve was also performed well with 0.9663 of the area under the ROC curve (AUC), which is better than all the features with 0.9423 of the AUC. Thus, it is proved that this novel method can reliably and accurately evaluate the effect of atorvastatin treatment. © 2016 SPIE.

关键词： Feature extraction

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Distributed optimization problem for second-order multi-agent networks with only position interaction 35

Distributed optimization problem for second-order multi-agen...

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第35届中国控制会议

作者： TRAN Ngoc-Tu LIU Xiao-Kang WANG Yan-Wu School of Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control(Huazhong University of Science and Technology) Ministry of Education Hubei Provincial Collaborative Innovation Center for New Energy Microgrid China Three Gorges University

ISBN: (纸本)9781509009107

In this paper, distributed optimization problem is investigated under a second-order multi-agent network, in which each agent is described as the double integrator. The multi-agent network is introduced for solving a large scale optimization problem by the cooperation of coupled agents. Based on the interaction over the network, the optimal solution of the problem can be obtained. Since the existing distributed algorithms for second-order multi-agent network enforce each agent to transmit complete information(both state information and derivation information of the independent variable, i.e., corresponded position and velocity information of the agent), this paper is motivated to design the distributed algorithm with only using the position information of neighbors, which reduces the requirement on communication bandwidth. With the help of Lyapunov analysis and La Sallel's Invariance Principle, the optimal solution is derived and the optimization problem is solved via the second-order multi-agent network. Finally, a numerical example is presented to illustrate the theoretical result.

关键词： Second-order multi-agent networks Distributed optimization Consensus

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A MIL-based interactive approach for hotspot segmentation from bone scintigraphy

A MIL-based interactive approach for hotspot segmentation fr...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Shijie Geng Jingyang Ma Xiaoguang Niu Shaoyong Jia Yu Qiao Jie Yang Institute of Image Processing and Pattern Recognition The Key Laboratory of System Control and Information Processing Ministry of Education China

ISBN: (纸本)9781479999897

Bone scintigraphy is widely used to diagnose bone diseases. Accurate hotspot segmentation is a critical task for tumor metastasis diagnosis. In this paper, we propose an interactive approach to detect and extract hotspots in thoracic region based on a new multiple instance learning (MIL) method called EM-MILBoost. We convert the segmentation problem to a multiple instance learning task by constructing positive and negative bags according to the input bounding box. In order to be robust against noisy input, we train a region-level hotspot classifier with EM-MILBoost and develop several segmentation strategies based on it. The experimental results demonstrate that our method outperforms other methods and is robust against various noisy input.

关键词： image segmentation Noise measurement Bones Training Indexes Belts Standards

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controllability of giant connected components in a directed network

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Physical Review E 2017年第4期95卷 042318-042318页

作者： Xueming Liu Linqiang Pan H. Eugene Stanley Jianxi Gao Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China Center for Polymer Studies and Department of Physics Boston University Boston Massachusetts 02215 USA School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou 450002 Henan China Center for Complex Network Research and Department of Physics Northeastern University Boston Massachusetts 02115 USA

When controlling a complex networked system it is not feasible to control the full network because many networks, including biological, technological, and social systems, are massive in size and complexity. But neither is it necessary to control the full network. In complex networks, the giant connected components provide the essential information about the entire system. How to control these giant connected components of a network remains an open question. We derive the mathematical expression of the degree distributions for four types of giant connected components and develop an analytic tool for studying the controllability of these giant connected components. We find that for both Erdős-Rényi (ER) networks and scale-free (SF) networks with p fraction of remaining nodes, the minimum driver node density to control the giant component first increases and then decreases as p increases from zero to one, showing a peak at a critical point p=pm. We find that, for ER networks, the peak value of the driver node density remains the same regardless of its average degree 〈k〉 and that it is determined by pm〈k〉. In addition, we find that for SF networks the minimum driver node densities needed to control the giant components of networks decrease as the degree distribution exponents increase. Comparing the controllability of the giant components of ER networks and SF networks, we find that when the fraction of remaining nodes p is low, the giant in-connected, out-connected, and strong-connected components in ER networks have lower controllability than those in SF networks.

关键词： Network structure

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Fuzzy control for Uncertain Vehicle Active Suspension Systems via Dynamic Sliding-Mode Approach

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2017年第1期47卷 24-32页

作者： Wen, Shiping Chen, Michael Z. Q. Zeng, Zhigang Yu, Xinghuo Huang, Tingwen School of Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China Department of Mechanical Engineering University of Hong Kong Hong Kong Hong Kong Platform Technologies Research Institute RMIT University MelbourneVIC3001 Australia Texas A and M University at Qatar Doha23874 Qatar

This paper investigates the fuzzy control issue for uncertain active suspension systems via dynamic sliding-mode method. The Takagi-Sugeno fuzzy approach is adopted on the background of the varying masses to describe the prescribed nonlinear system in order to achieve the design targets via the method of sector nonlinearity. This paper employs the dynamic sliding-mode scheme to control nonlinear active suspension systems. In the proposed sliding-mode control scheme, the sliding surface function is formed linearly with the system states and control inputs. Then, a fuzzy dynamic term is utilized to construct the sliding-mode feedback controller. In existing results, the sliding mode is achieved and maintained with no consideration of the system perturbations. Thus, sufficient conditions are proposed to make the sliding surface reachable with the existence of the system perturbations to make the augmented system stable. Finally, simulation results are presented to verify the effectiveness of the proposed schemes. © 2013 IEEE.

关键词： Robust control

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Brain MRI Segmentation with Patch-based CNN Approach

Brain MRI Segmentation with Patch-based CNN Approach

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第35届中国控制会议

作者： Zhipeng CUI Jie YANG Yu QIAO Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University The Key Laboratory of Ministry of Education for System Control and Information Processing

ISBN: (纸本)9781509009107

Brain Magnetic Resonance image(MRI) plays a non-substitutive role in clinical *** symptom of many diseases corresponds to the structural variants of *** structure segmentation in brain MRI is of great importance in modern medical *** methods were developed for automatic segmenting of brain MRI but failed to achieve desired *** this paper,we proposed a new patch-based approach for automatic segmentation of brain MRI using convolutional neural network(CNN).Each brain MRI acquired from a small portion of public dataset is firstly divided into *** of these patches are then used for training CNN,which is used for automatic segmentation of brain *** results showed that our approach achieved better segmentation accuracy compared with other deep learning methods.

关键词： CNN Deep Learning Brain MRI Segmentation Patch-based

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Online Calibration of Intracortical Neural Interface Based on Transfer Learning

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Journal of Physics: Conference Series 2018年第1期1069卷

作者： Bo Peng Wei Li Jiping He School of Automation Huazhong University of Science and Technology Wuhan 430074 P. R. China Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Wuhan 430074 P. R. China Department of Mechanical Engineering Beijing Institute of Technology Beijing 100081 P. R. China

In the application of neural interface, the neural activity of neurons and neuronal groups is not fixed even under the same task conditions. Meanwhile, the recording conditions of neural signals are also very unstable, with a high degree of within-and across-day variability. This results in a very unstable firing pattern for the recorded neural spike signals. In order to get better performance, the decoder often requires a lot of online calibration samples. This brings a heavy training burden to neural interface users. To solve this problem, this paper proposes to apply transfer learning (TL) to online calibration of intracortical neural interface to reduce the dependence of decoder on a large number of online calibration samples. Experimental results show that through transferring from a large amount of historical data, decoder can achieve satisfactory classification accuracy with only a small amount of online data.

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Objective resolution measurement in single particle reconstructions based on a new spectral signal-to-noise ratio estimation

Objective resolution measurement in single particle reconstr...

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第28届中国控制与决策会议

作者： Shuai Wang Biao Zhang Hong-Bin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

ISBN: (纸本)9781467397155

The resolution measurement of 3D reconstructed density map in single particle reconstruction is an important and still an open *** this paper,we propose a new protocol to measure the resolution just from the reconstructed density *** approach estimates spectral signal-to-noise ratio(SSNR) of 3D reconstructed map by computing the ratio of signal power to noise power in frequency *** power distributions of signal and noise are estimated from structure particle region and surrounding region segmented by applying a mask *** proposed protocol of calculating SSNR,which we term mask-SSNR(mSSNR),is independent of the reconstruction algorithms and can be used for density maps reconstructed with any reconstruction ***,the mSSNR neither needs to split the dataset into halves like the Fourier shell correlation(FSC) approach,nor any original images or intermediate data like other SSNR calculation methods in this *** mSSNR provides a direct calculation of SSNR based on its original definition,and is proven to be a better approach.

关键词： Electron microscopy Resolution measurement Spectral signal-to-noise ratio Signal processing

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Research on walking-aid robot motion control with both compliance and safety

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Zidonghua Xuebao/Acta Automatica Sinica 2016年第12期42卷 1859-1873页

作者： Xu, Wen-Xia Huang, Jian Yan, Qing-Yang Wang, Yong-Ji Tao, Chun-Jing Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan430074 China National Rehabilitation Center Beijing100176 China

Aimed at compliance and safety problems in motion control of walking-aid robot, a multi-sensor fusion based walking-aid robot motion control method with both compliance and safety is proposed. Firstly, the mechanism, control theory and multi-sensor system of the walking-aid robot are introduced. Then according to multi-sensor system, user motion intention estimation methods for each sensor are designed and a multi-sensor based compliance motion control for walking-aid robot is proposed. After analyzing user's possible falling modes, a Kalman filter (KF) based sequential probability ratio test (SPRT) method and decision function are used to detect the fall and falling mode. Finally, several compliance motion control experiments and fall detection experiments are described to show validity of the proposed algorithm. Copyright © 2016 Acta Automatica Sinica. All rights reserved.

关键词： Robots

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