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Connectivity Exploration after Stroke with Structural Equation Modeling

Connectivity Exploration after Stroke with Structural Equati...

引用

2012 Third International Conference on Theoretical and Mathematical Foundations of Computer Science(ICTMF 2012)

作者： Wei Li Hongtao Tan Xiaojun Wang Zhiqiao Yan Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of ChinaHuazhong University of Science and Technology

Neuroplasticity has been demonstrated to play an important role in function recovery *** this paper,stroke patients and controls were subjected to functional magnetic resonance imaging(fMRI) study for *** group independent componentanalysis was used to get the time courses of the interested regions in *** investigate the reorganization of cerebral cortex after stroke,Structural Equation Modeling(SEM) was applied to construct a locomotor brain network *** results were analyzed to investigate thebrain activity changes involved in the cerebral motor cortex circuitry aroused by the hand *** contrast to healthy people,we found that the brain activity changes of the stroke patientscould not onlyshow the local changes around injured regions,but also the global transformation of brain related to *** the differences were examined in terms of changes in path coefficients between brain regions.

关键词： fMRI,ICA,SEM,Stroke,Neuroplasticity

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Implementation of Memristive Neural Networks with Spike-rate-dependent Plasticity Synapses

Implementation of Memristive Neural Networks with Spike-rate...

引用

International Joint Conference on Neural Networks

作者： Yide Zhang Zhigang Zeng Shiping Wen School of Automation Huazhong University of Science and Technology and Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China

ISBN: (纸本)9781479914821

The property of changing resistance according to applied currents of memristors makes them candidates for emulating synapses in artificial neural networks. In this paper, we introduce a memristive synapse design into neural network circuits. Combined with modified integrate-and-fire (I&F) complementary metal-oxide-semiconducter (CMOS) neurons, the memristive neural network shows similarities to its biological counterpart, in respect of biologically realistic, current-controlled spikes and adaptive synaptic plasticity. Then, the spike-rate-dependent plasticity (SRDP) of the synapse, an extended protocol of the Hebbian learning rule, is originally implemented by the circuit. And some advanced neural activities including learning, associative memory and forgetting are realized based on the SRDP rule. These activities are comprehensively validated on a neural network circuit inspired by famous Pavlov's dog-experiment with simulations and quantitative analyses.

关键词： Neurons Memristors Biological neural networks Biological system modeling Protocols Semiconductor device modeling Integrated circuit modeling

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SliceProp: A Slice-Wise Bidirectional Propagation Model for Interactive 3D Medical image Segmentation 1

SliceProp: A Slice-Wise Bidirectional Propagation Model for ...

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1st IEEE International Conference on Medical Artificial Intelligence, MedAI 2023

作者： Xu, Xin Lu, Wenjing Lei, Jiahao Qiu, Peng Shen, Hong-Bin Yang, Yang Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Shanghai Ninth People's Hospital Shanghai Jiao Tong University School of Medicine Department of Vascular Surgery China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9798350358780

Interactive medical image segmentation methods have become increasingly popular in recent years. These methods combine manual labeling and automatic segmentation, reducing the workload of annotation while maintaining high accuracy. However, most current interactive segmentation frameworks are limited to 2D image data, and are not suitable for 3D image data due to the large size and high complexity of 3D data, as well as the challenges posed by information asymmetry and sparse annotation. In this paper, we propose SliceProp, an interactive segmentation framework that implements slice-wise Label Bidirectional Propagation (LBP) for 3D medical image segmentation. SliceProp extends the interactive 2D image segmentation algorithm to 3D image segmentation, and can handle 3D data with large size and high complexity. Moreover, equipped with a Backtracking Feedback Check (BFC) module, SliceProp effectively addresses the issues of information asymmetry and spatial sparse annotation in 3D medical image segmentation. Additionally, we adopt an uncertainty-based criterion to pri-oritize the slices to be refined interactively, which enhances the efficiency of the interaction process by enabling the model to focus on the regions with the most unreliable predictions. SliceProp is evaluated on two datasets and achieves promising results compared to state-of-the-art methods. © 2023 IEEE.

关键词： Medical imaging

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The study on Dynamics of Functional Brain network:Based on Symbolic Dynamics

The study on Dynamics of Functional Brain network:Based on S...

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第28届中国控制与决策会议

作者： Miao Wang Yapeng Li Xi Chen Wei Li College of Automation Huazhong University of Science and Technology Image Processing and Intelligent Control Key Laboratory of Education Ministry of China

ISBN: (纸本)9781467397155

It is an important means to reveal mysteries of the brain with information theory,but scientists rarely use this method for the study of the nervous system in recent *** this study,it's the first time,by using the concepts of information theory,to exploratory investigate the dynamic properties of time course data of fMRI and functional brain *** show that the symbolic dynamics method can reduce the noise of the MRI datasets,and highlight the differences between the *** elderly group,the regions with larger entropy are mainly located in prefrontal regions,basal ganglia ***,there are significant differences in the search information entropy between the young and elderly *** results have significance for the interpretation of the brain mechanisms,which may be the basis for follow-up studies of the brain mechanisms.

关键词： fMRI Symbolic dynamics Probabilistic entropy Search information entropy

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A Comparison of Large-Scale MOEAs with Informed Initialization for Voltage Transformer Ratio Error Estimation 1

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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Li, Lianghao He, Cheng Li, Hongbin Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Large-scale multiobjective optimization problems (LSMOPs) exist widely in real-world applications. The large number of decision variables in LSMOP leads to a tremendous high-dimensional search space, which is still challenging for existing multiobjective evolutionary algorithms (MOEAs). The voltage transformer ratio error estimation (TREE) problem is a typical LSMOP in real-world applications. A number of large-scale multiobjective evolutionary algorithms (LSMOEAs) have been adopted for solving the TREE problem, but so far there is still considerable potential for improvement in their results. In this paper, we propose a informed initialization for solving the TREE problem. The physical properties of the TREE problem are used to construct an initial set of solutions with specific characteristics. The proposed initialization method is tested against the default initialization method on five TREE problems by being applied on six state-of-the-art LSMOEAs and a classical MOEA. The experimental results demonstrate that the initialization method has a significant effect on the performance of LSMOEAs in solving the TREE problems. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multiobjective optimization

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Mid-level parts mined by feature selection for action recognition

Mid-level parts mined by feature selection for action recogn...

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Asian Conference on Pattern Recognition (ACPR)

作者： ShiWei Zhang Nong Sang ChangXin Gao FeiFei Chen Jing Hu Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology China

ISBN: (纸本)9781479961016

This paper develops a method to learn very few discriminative part detectors from training videos directly, for action recognition. We hold the opinion that being discriminative to action classification is of primary importance in selecting part detectors, not just intuitive. For this purpose, part selection based on feature selection is proposed, employing SVM method. Firstly, large number of candidate detectors are trained using k-means and Exemplar-LDA techniques in whitened feature space. Secondly, each candidate part detector is regarded as a visual feature, so that detector selection can be achieved by feature selection. Detectors with larger weight, indicating more discriminative, will be selected. Meanwhile, to keep space-volume structure information, we use the novel method saliency-driven pooling to form feature primitives which are concatenated into mid-level feature vector. Finally, we conduct experiments on three challenging action datasets (KTH, Olympic Sports, HMDB51) and the results outperform the state-of-the-art.

关键词： Detectors Feature extraction Videos Support vector machines Semantics Pattern recognition image recognition

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CPTNet: Cascade Pose Transform Network for Single image Talking Head Animation 15th

CPTNet: Cascade Pose Transform Network for Single Image Talk...

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15th Asian Conference on Computer Vision, ACCV 2020

作者： Zhang, Jiale Xian, Ke Liu, Chengxin Chen, Yinpeng Cao, Zhiguo Zhong, Weicai Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Huawei CBG Consumer Cloud Service Search Product and Big Data Platform Department Xi’an China

ISBN: (纸本)9783030695378

We study the problem of talking head animation from a single image. Most of the existing methods focus on generating talking heads for human. However, little attention has been paid to the creation of talking head anime. In this paper, our goal is to synthesize vivid talking heads from a single anime image. To this end, we propose cascade pose transform network, termed CPTNet, that consists of a face pose transform network and a head pose transform network. Specifically, we introduce a mask generator to animate facial expression (e.g., close eyes and open mouth) and a grid generator for head movement animation, followed by a fusion module to generate talking heads. In order to handle large motion and obtain more accurate results, we design a pose vector decomposition and cascaded refinement strategy. In addition, we create an anime talking head dataset, that includes various anime characters and poses, to train our model. Extensive experiments on our dataset demonstrate that our model outperforms other methods, generating more accurate and vivid talking heads from a single anime image. © 2021, Springer Nature Switzerland AG.

关键词： Animation

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A Point Cloud Segmentation Method Based on Ground Point Cloud Removal and Multi-Scale Twin Range image 42

A Point Cloud Segmentation Method Based on Ground Point Clou...

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42nd Chinese control Conference, CCC 2023

作者： Zhou, Yicheng Peng, Gang Duan, Hangqi Wu, Zhangang Zhu, Xukang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan430074 China Shantui Construction Machinery Co. Ltd. Jining272073 China

ISBN: (纸本)9789887581543

Aiming at the shortcomings of traditional point cloud segmentation algorithms, this paper proposes a 3D lidar point cloud segmentation method combining ground filtering and multi-scale twin range image construction. This method fully considers the geometric space distribution characteristics of the point cloud and the randomness of the positions between objects. Based on the assumption of multi plane model, the point cloud is divided into sectors. The ground points are removed through region ground plane fitting and growth, and then the multi-scale twin range image is constructed according to non-ground points. On the basis of the twin range image, the Breadth First Search algorithm is improved, the depth-breadth joint search strategy is proposed, all the points to be clustered are traversed, and the adaptive clustering threshold is used for point cloud clustering, which realizes a point cloud segmentation method with higher accuracy and robustness. Through the experimental analysis of KITTI dataset and collected campus outdoor scene dataset, compared with the traditional point cloud segmentation algorithm, the method proposed in this paper can effectively improve the point cloud segmentation accuracy and robustness of mobile robots in complex environments. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： image enhancement

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A Tube Length Measurement Device Based on Acoustic Method

A Tube Length Measurement Device Based on Acoustic Method

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International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Yimin Chen Jian Qi Xuming Zhang Mingyue Ding Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

A low-cost device using acoustic method for measuring open-end tube length is developed. The proposed device is aimed to get the length of the tubes which are piled up together, and only one end of which is available in the warehouse or dumping areas. The device contains the emitting and receiving probes to echo the sound pulse and receive the reflection sound wave, and has been developed with discrete component circuits whose key part is the logical control circuit based on ARM. Experiments are performed in the open tubes with the lengths between 0.85 m to 6 m. The measurement error is below 0.5 cm. For the tubes blocked by the cement or earth, the device can detect the location of obstruction automatically. Based on the acoustic method, experiments are also conducted in the blocked tubes based on Matlab software, and the analysis of the reflection wave is given.

关键词： Electron tubes Length measurement Acoustics Acoustic measurements Calibration Earth Measurement uncertainty

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Event-triggered consensus of nonlinear multi-agent systems with nonlinear interconnections

Event-triggered consensus of nonlinear multi-agent systems w...

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Chinese control Conference (CCC)

作者： Xiuxia Yin Dong Yue Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei CN

This paper investigates the consensus problem for a set of nonlinear multi-agent systems with nonlinear interconnections. First, in order to reduce the communication burden in the multi-agent network, a distributed event-triggered consensus control is designed by taking into account the effect of the nonlinear interconnections. Then, based on the Lyapunov functional method and the Kronecker product technique, sufficient conditions are obtained to guarantee the consensus in the form of linear matrix inequality (LMI). Finally, a simulation example is proposed to illustrate the effectiveness of the developed theory.

关键词： Tin Multi-agent systems control design Lead Bandwidth Ear Nickel

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