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第41届中国控制会议

作者： Yu Zhai Zhe Liu Yanzi Miao Hesheng Wang China University of Mining and Technology MoE Key Lab of Artificial Intelligence Shanghai Jiao Tong University Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Developing an efficient automatic navigation system for mobile robots is challenging in the strange scenarios where robots can only observe the environment of the surrounding limited *** other distributed automatic navigation systems exist,they often require extracting semantic information to calculate navigation action,which requires extra modules to provide perceptual information and is not *** propose an end-to-end automatic navigation system based on the reinforcement learning *** particular,the raw 3 D LiDAR data is used to directly map an efficient navigation *** design a novel dense reward function to handle the reward sparsity issue and provide a graphical representation method to enable the efficient feature learning from the raw 3 D LiDAR data in our navigation *** addition,an imitation learning based policy initialization is introduced before the subsequent reinforcement learning,which increases the learning efficiency and,in the meantime,still encouraging the robot to explore all the potential states to achieve advanced performance than the imitated *** navigation model is trained in the Webots environment and the experimental results show that our model has efficient and flexible navigation performance in complex *** importantly,trained model can be easily extended to unfamiliar environments.

关键词： End-to-end Navigation Mobile robot Reinforcement Learning 3D LiDAR

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image enhancement based on intrascale dependencies of the second generation curvelet transform

Image enhancement based on intrascale dependencies of the se...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Hao, Hongxia Liu, Fang Jiao, Licheng School of Computer Science and Technology Xidian University Xi'an 710071 China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Xi'an 710071 China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478092

This paper presents a strong noise image enhancement method based on intrascale dependencies of the second generation curvelet transform. Observing that the immediate four neighbor coefficients bear the most important dependencies, we use spatial clustering property of the intrascale neighbor coefficients to separate noise and signal of interest, and to deal with them differently, i.e. to suppress noise and strengthen edges. Comparing our approach with Starck's enhancement model (Starck et al., 2003), we experimentally find that for high noise level images, our method outperforms the starck's system in noise suppression and signal strengthening and produces better enhancement results. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image enhancement

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Automatic detection of the intima-media layer in ultrasound common carotid artery image based on active contour model

Automatic detection of the intima-media layer in ultrasound ...

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2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Jin, Jiaoying Ding, Mingyue Yang, Xin Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Life School of Science and Technology Huazhong University of Science and Technology Wuhan China State Key Laboratory for Multi-spectral Information Processing Technologies Life School of Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769546230

The analysis of the carotid artery wall is of paramount importance in clinical practice. Especially, the intima-media thickness is a risk index for some of the most severe acute cerebrovascular pathologies, hence, an accurate segmentation of the different layers of the carotid artery is needed. IMT is usually manually measured on longitudinal B-mode ultrasound images. In the past ten years, many computer-based techniques for intima-media thickness measurement have been proposed to overcome the limits of manual segmentation, but almost all of them require a certain degree of user interaction. In this paper we proposed a novel approach for the completely user-independent segmentation of the common carotid artery wall. Our algorithm is designed for the extraction of the intima and media layers of the distal carotid wall in ultrasound images. It is based on integrated approach consisting of common carotid artery region identification, contour initialization with threshold segmentation, intima-lumen segmentation with Snake, and media-adventitia segmentation with GVF-Snake that enables the automated tracing of the carotid walls. The acoustic impedance's difference is employed to locate common carotid artery region. Finally, the characterization of the algorithm in terms of segmentation error was evaluated with a set of 40 common carotid artery ultrasound images and compared to the segmentation traced by a trained operator. Experiments showed that a mean error lower than 1.3 pixel both on the intima and media layers was obtained, which is comparable to that obtained by means of operator dependent techniques. © 2011 IEEE.

关键词： image segmentation

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On the periodic dynamics of memristor-based neural networks with time-varying delays

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Information Sciences 2014年 279卷 358-373页

作者： Jiejie Chen Zhigang Zeng Ping Jiang School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education Wuhan 430074 China

In this paper, we study the existence, uniqueness and stability of periodic solution for a wide class of memristor-based neural networks with time-varying delays. By employing the topological degree theory in set-valued analysis, differential inclusions theory and a new Lyapunov function method, we prove that the neural network has a unique periodic solution, which is globally exponentially stable. Moreover, we prove the existence, uniqueness and global exponential stability of equilibrium point for time-varying delayed memristor-based neural networks with constant coefficients. The obtained results improve and extend previous works on memristor-based or usual neural network dynamical systems with continuous or discontinuous right-hand side. Finally, two numerical examples are provided to show the applicability and effectiveness of our main results.

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Smart Power Safety Hazard Inspection System Based on YOLOv7 1st

Smart Power Safety Hazard Inspection System Based on YOLOv7

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1st International Conference on Applied Intelligence, ICAI 2023

作者： Liang, Yiheng Li, Xiaoming Deng, Zhenrong School of Computer and Information Security Guilin University of Electronic Technology Guilin541004 China Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9789819708260

Power safety is closely related to people’s well-being. Electric power sectors regularly inspect and maintain power lines to guarantee people’s safe and stable use of electricity, and the current mainstream inspection method is to use UAVs for power inspection. Traditional inspection and detection methods have many shortcomings, such as high labor costs, slow inspection speed, low detection efficiency, and single detection targets. In this paper, a set of smart power inspection systems based on YOLOv7 was designed to check the common potential security risks of power lines such as bird nests, insulators, garbage, and hardware. After the detection, the detection report could be generated. The system adopted the YOLOv7 target detection algorithm. The accuracy rate of all detection targets was up to 93.9%, and the mAP @.5% reached 95.9%. Therefore, the algorithm could greatly improve the detection efficiency and greatly facilitate the electric power sectors to check power lines, so it has a high use value. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Inspection

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Parallel Generate Entry Landing Footprint Using Differential Evolution

Parallel Generate Entry Landing Footprint Using Differential...

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International Symposium on Computer, Consumer and control (IS3C)

作者： Songtao Chang Yongji Wang Lei Liu Department of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

Landing footprint of an entry vehicle provides critical information for mission planning. Conventional methods calculate it through solving a family of multi-constraints optimal control problems. It is difficult to solve. To generate the boundary of it, we proposed a new scheme based on differential evolution(DE). Utilizing DE's parallelism, each run generates one side instead of one point of the boundary. To get the full boundary, just need run the algorithm two times. The algorithm's merits include accurate, fast, not relying on simplification of the system, all control variables are under consideration and facilitating parallel programming.

关键词： Vehicles Vehicle dynamics Optimal control Vectors Trajectory Optimization Heuristic algorithms

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Non-intrusive load monitoring based on a combination of Transformer and CNN 4

Non-intrusive load monitoring based on a combination of Tran...

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4th International Conference on Energy, Power and Electrical Engineering, EPEE 2024

作者： Cheng, Yiqi Zhong, Yanru Guilin University of Electronic Technology College of Computer and Information Security Guangxi Guilin China Guilin University of Electronic Technology Guangxi Key Laboratory of Image And Graphic Intelligent Processing Guangxi Guilin China

ISBN: (纸本)9798331518066

Non-intrusive load monitoring (NILM) estimates the energy usage of individual devices by analyzing the total power meter data from a household. To address the issue of decreased monitoring accuracy with an increasing number of electricity meters, this paper proposes a solution for single appliance load monitoring (Tra-CNN). The solution uses the UK-DALE dataset, which contains high and low frequencies electricity consumption data of multiple households in the UK and the electricity consumption data of each household appliance, and uses the active power of the appliance as the input of the algorithm. The first part of the model consists of a convolutional layer, a normalization layer, and a dropout layer, with the primary task of capturing local dependencies in the data. The second part consists of a Transformer, whose self-attention mechanism associates features at different positions in the sequence to achieve modeling of long-term dependencies. The third part introduces a convolutional neural network, which uses a sliding window for convolution operations to extract local features from different positions and further extract features from sequence data. The final decoder consists of a transposed convolutional layer and a normalization layer, designed to revert the learned features to their original dimensions. Through experimental verification, the effectiveness and superiority of Tra-CNN are shown, which provides important ideas and methods for the further development of NILM technology. © 2024 IEEE.

关键词： Convolution

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Decoupling guaranteed cost control of BTT vehicle based on LMI

Decoupling guaranteed cost control of BTT vehicle based on L...

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IEEE International Conference on intelligent Computing and intelligent Systems (ICIS)

作者： Zhixiang Deng Yongji Wang Lei Liu Chuanfeng Li Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424447374;9781424447541

This paper presents a new approach for coupling control problems for norm bounded continuous-time uncertain systems. Firstly, a design of the state feedback decoupling controller is presented. The nominal model could be decoupled completely and the coupling of the actual system would be reduced. Secondly, based on the linear matrix inequality (LMI), combining the guaranteed cost control law with the decoupling control, the state feedback tracking guaranteed cost control law is proposed. Finally, taking BTT vehicle as the research objective, the design procedure of the decoupling guaranteed cost controllers is shown and the final results of the simulation are proved with effectiveness for the proposed design approach.

关键词： Costs Vehicles control systems Uncertain systems Robust control State feedback Linear matrix inequalities Linear feedback control systems Uncertainty Missiles

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Wind Vector Inversion of ADS-B Data Based on Improved PSO-PF Algorithm

Wind Vector Inversion of ADS-B Data Based on Improved PSO-PF...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Chen, Wantong Wu, Duo Ren, Shiyu Diao, Tianru Tianjin Key Laboratory of Intelligent Signal and Image Processing Civil Aviation University of China Tianjin300300 China School of Electronic Information and Automation Civil Aviation University of China Tianjin300300 China

ISBN: (纸本)9789811966125

At present, inversing wind vector from aircraft trajectory captured by automatic dependent surveillance-broadcast (ADS-B) is one of the main solutions to obtain wind field in aviation meteorology. However, some algorithms in this scheme still have some shortcomings, especially the poor performance when the aircraft turns at a small angle. In this paper, the geometric structure of ADS-B data is used to improve particle swarm optimized particle filter algorithm (PSO-PF) to inverse wind vectors in small area of single aircraft data and large area of multi-aircraft data respectively. The mean absolute error of wind estimation under different turning angles is evaluated. Experimental results show that the algorithm is feasible, and it still has a good inversion effect when the aircraft turns at a small angle. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Aircraft

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Constrained trajectory optimization using migrant particle swarm optimization algorithm

Constrained trajectory optimization using migrant particle s...

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Fuqiang Xie Yongji Wang Zongzhun Zheng Da Zhang Department of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

A novel PSO algorithm, the Migrant Particle Swarm Optimization (Migrant PSO), is presented to solve the trajectory optimization problem in the presence of constraints such as dynamic pressure and overload. Imitating the behaviour of a flock of migrant birds, the Migrant PSO algorithm employs stochastic search method and adaptive linear search method respectively for PSO search spaces including both continuous space and discrete space. In the example of the minimum peak heat rate reentry trajectory optimization for X-33 vehicle model with free terminal time, some key problems such as parameterized method are argued in detail. The simulation results indicate that the Migrant PSO algorithm proves to be able to generate a complete and optimal 3DOF reentry trajectory rapidly.

关键词： Constraint optimization Particle swarm optimization Stochastic processes Ant colony optimization Optimization methods Search methods Space vehicles Pressure control Birds Optimal control

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