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Image retrieval based on convolutional neural network and linear discriminate analysis

IOP Conference Series: Materials Science and Engineering 2019年第5期569卷

作者： Wei Xia Cong Hu Xianghui Cheng Peng Chen Xing Jin School of Automation China University of Geosciences Wuhan 430074 China Hubei key laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan 430074 China

Image retrieval is a hot research topic in the field of computer vision image processing, and the user queries the image database for similar images and produces a list of recommendations. The paper firstly sets forth the research status of image retrieval, then the convolution neural network is briefly introduced. Due to the traditional image retrieval and recommendation system use manual extraction of image features is relatively cumbersome, and the retrieval accuracy is not high research status, the paper proposes an image retrieval method based on the improved convolutional neural network and linear discriminate analysis. Caltech256 and CIFAR-10 datasets were trained using the model in this paper, experimental, results show that the proposed method can effectively improve the performance of retrieval.

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Stabilization of a class of fractional order chaotic systems by nonlinear sliding mode

Stabilization of a class of fractional order chaotic systems...

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第37届中国控制会议

作者： Lijun Lin Yongzhi Sheng School of Automation Beijing Institute of Technology Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology

This paper investigates the stabilization problem of a class of fractional order chaotic systems with unknown modeling uncertainties and external perturbations. A fractional nonlinear sliding surface is proposed, and a reaching control law is obtained to guarantee the stability of the fractional chaotic system in finite time with just a single control input. And the simulation results are given to demonstrate the efficacy of the proposed nonlinear sliding mode control method.

关键词： Fractional order Chaotic system Nonlinear sliding mode Stabilization

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Flocking of Second-Order Multiagent systems with Connectivity Preservation Based on Algebraic Connectivity Estimation

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IEEE Transactions on Cybernetics 2017年第4期47卷 1067-1077页

作者： Fang, Hao Wei, Yue Chen, Jie Xin, Bin School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

The problem of flocking of second-order multiagent systems with connectivity preservation is investigated in this paper. First, for estimating the algebraic connectivity as well as the corresponding eigenvector, a new decentralized inverse power iteration scheme is formulated. Then, based on the estimation of the algebraic connectivity, a set of distributed gradient-based flocking control protocols is built with a new class of generalized hybrid potential fields which could guarantee collision avoidance, desired distance stabilization, and the connectivity of the underlying communication network simultaneously. What is important is that the proposed control scheme allows the existing edges to be broken without violation of connectivity constraints, and thus yields more flexibility of motions and reduces the communication cost for the multiagent system. In the end, nontrivial comparative simulations and experimental results are performed to demonstrate the effectiveness of the theoretical results and highlight the advantages of the proposed estimation scheme and control algorithm. © 2017 IEEE.

关键词： Multi agent systems

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Micro Channel for Analyzing Mechanical Adaption of Cancer Cell

Micro Channel for Analyzing Mechanical Adaption of Cancer Ce...

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IEEE International Conference on Cyborg and Bionic systems (CBS)

作者： Pengyun Li Xiaoming Liu Xiaoqing Tang Masaru Kojima Jian Huang Qiang Huang Tatsuo Arai Beijing Advanced Innovation Center for Intelligent Robots and Systems and the Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Osaka University 1-3 Machikaneyama Toyonaka Osaka Japan Key Laboratory of Ministry of Education for Image Processing and Intelligent Control the School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781728150734

ISBN: (纸本)9781728150741

It was reported that cancer cells could biologically respond and adapt to the confined environment during migration in extracellular matrix (ECM). But it is not clearly studied that how cancer cells respond and adapt to confined environment in mechanical way. Thus, in this study, we designed and fabricated a kind of one-layer micro channel to mimic confined environment for analyzing mechanical adaption of cell. This micro channel could apply sequential mechanical stresses on a number of cells with high throughput, and the time of cells passing through five rows of micro channels were used to evaluate their adaptability to the sequential and confined space. In experiments, each cell suffered 20 times of mechanical stresses after passing through 20 squeezing channels arranged in 5 rows. We observed the sequential squeezing processes under microscope and investigated the passing time using a high-speed camera. The preliminary results indicated that cancer cells could pass through and adapt to the confined environment faster than normal cells.

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Evolutionary Design of controllers with Optimized Structure and Its Application in a Maglev Ball control System 36

Evolutionary Design of Controllers with Optimized Structure ...

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第36届中国控制会议

作者： Zhan Jiaoyang Xin Bin Chen Jie School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology

ISBN: (纸本)9781538629185

In order to realize the flexible automatic design of controllers, this paper proposes a library-based controller design method with bi-level optimization of structure and parameters. The controller with optimized structure is composed by components which are selected from a component library. A binary string is used to express a controller structure, where each bit represents the connection relationship between two links. The controller structure and parameters are optimized in a hierarchical manner by the binary Geometric Differential Evolution Algorithm in the outer layer and an advanced Differential Evolution algorithm variant named JADE in the inner layer, respectively. Simulation and experiment of a magnetic levitation ball control system have been done to verify the performance of the presented controller. Results demonstrate the feasibility and superiority of the proposed method.

关键词： Optimal Design of controllers Structural Optimization Library-based controller Design intelligent Optimization Differential Evolution

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Multi Constellation Fast Selection Method Based on Equivalent Distance Error

Multi Constellation Fast Selection Method Based on Equivalen...

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第37届中国控制会议

作者： Guangjun Wang Yutao Cheng Shaohui Yang School of Automatic China University of Geosciences Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Systems STATE GRID PUYANG ELECTRIC POWER SUPPLY COMPANY

A single satellite navigation system can get high accuracy in general environment, but when the ground satellite navigation receiver is in complex environment, single system navigation often results in poor location results due to the visible satellite less than four. If multiple constellation fusion navigation is used, the number of visible satellites can be increased, thus improving the positioning results. However, the use of all visible satellites in location calculation will bring a huge amount of calculation, which seriously affects the real-time performance of navigation and positioning. Therefore, a reasonable selection of star selection method is urgently needed in the integrated navigation system. Based on the two performance indexes of balanced geometric accuracy factor（GDOP） and star selection efficiency, fast star selection algorithm based on equivalent distance error is proposed in this paper. The experimental results show that the method can effectively improve the efficiency of multi constellation star selection of the premise of high precision.

关键词： Satellite navigation Multi-constellation fusion Satellite selection Geometric Dilution of Precision

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Fault Tolerant control for a Class of Nonlinear System based on Active Disturbance Rejection control and RBF Neural Networks 36

Fault Tolerant Control for a Class of Nonlinear System based...

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第36届中国控制会议

作者： Lushan Zhou Liling Ma Junzheng Wang State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

ISBN: (纸本)9781538629185

In this paper,a fault tolerant control method based on active disturbance rejection control(ADRC) and radial basis function neural network(RBFNN) is proposed for a class of multi-input-multi-output nonlinear system with actuator faults,components faults and sensor *** proposed method does not rely on the plant *** regarding the faults and plant uncertainties as the disturbance,through the observation of extended state observer and the compensation of feedback control signal,this method achieves the fault tolerance control of the plant with component fault and actuator *** sensor faults,in this work,radial basis function neural network is applied to estimate the real output of the *** this output estimation is utilized by active disturbance rejection control to achieve the fault tolerance of ***,the effectiveness of the proposed method is validated by the simulation results of the three-tank system.

关键词： Fault tolerant control active disturbance rejection control radial basis function neural network

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Fault Detection of a 6-DOF Hydraulic Platform Based on Equivalent-Input-Disturbance Approach 29

Fault Detection of a 6-DOF Hydraulic Platform Based on Equiv...

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第29届中国控制与决策会议

作者： Qianqiu Li Jinhua She Min Wu Pingping Lin School of Information Science and Engineering Central South University School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

ISBN: (纸本)9781509046584

This paper presents a method of fault detection for a 6-degree-of-freedom hydraulic platform based on the equivalent-input-disturbance(EID) ***,a model of the platform is derived based on the Lagrange ***,the types of actuator faults are ***,an optimal feedback controller is designed and the EID approach is incorporated to detect and suppress actuator *** results demonstrate the effectiveness of the method.

关键词： Equivalent input disturbance 6 degrees of freedom Fault detection Optimal feedback controller

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Decoupling control for Parallel Robot Based on Equivalent-Input-Disturbance Approach 29

Decoupling Control for Parallel Robot Based on Equivalent-In...

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第29届中国控制与决策会议

作者： Pingping Lin Jinhua She Min Wu Qianqiu Li School of Information Science and Engineering Central South University School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

ISBN: (纸本)9781509046584

This paper discusses the problem of posture control for a parallel *** parallel robot features multiple variables and large *** control accuracy is strongly affected by the parameters which are coupled with each other,and by exogenous disturbances.A decoupling control strategy is presented based on the equivalent-inputdisturbance(EID) approach to improve control ***,decoupling control is used to eliminate the main coupling effect between multiple ***,the EID method is used to further improve decoupling effect and suppress the external *** results show that the control strategy is effective for the decoupling control of parallel robot.

关键词： Parallel Robot Decoupling control Equivalent Input Disturbance(EID) PID

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Global Rice Multi-Class Segmentation Dataset (RiceSEG): A Comprehensive and Diverse High-Resolution RGB-Annotated Images for the Development and Benchmarking of Rice Segmentation Algorithms

arXiv

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arXiv 2025年

作者： Zhou, Junchi Wang, Haozhou Kato, Yoichiro Nampally, Tejasri Rajalakshmi, P. Balram, M. Katsura, Keisuke Lu, Hao Mu, Yue Yang, Wanneng Gao, Yangmingrui Xiao, Feng Chen, Hongtao Chen, Yuhao Li, Wenjuan Wang, Jingwen Yu, Fenghua Zhou, Jian Wang, Wensheng Hu, Xiaochun Yang, Yuanzhu Ding, Yanfeng Guo, Wei Liu, Shouyang Engineering Research Center of Plant Phenotyping Ministry of Education Jiangsu Collaborative Innovation Center for Modern Crop Production Academy for Advanced Interdisciplinary Studies Sanya Institute of Nanjing Agricultural University Nanjing Agricultural University Nanjing China Graduate School of Agricultural and Life Sciences The University of Tokyo Tokyo Japan Department of Artificial Intelligence Indian Institute of Technology Hyderabad India Department of Electrical Engineering Indian Institute of Technology Hyderabad India Institute of Biotechnology Professor Jayashankar Telangana Agricultural State University Hyderabad India Graduate School of Agriculture Kyoto University Kyoto Japan Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene Research Hubei Key Laboratory of Agricultural Bioinformatics Huazhong Agricultural University Wuhan China State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China the Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing China Center for Geospatial Information Shenzhen Institutes of Advanced Technology Chinese Academy of Science Shenzhen China School of Information and Electrical Engineering Shenyang Agricultural University Shenyang China Rice Research Institute Jilin Academy of Agricultural Sciences Changchun China Institute of Crop Sciences National Key Facility for Crop Gene Resources and Genetic Improvement Chinese Academy of Agricultural Sciences Beijing China Yuan Long Ping High-Tech Agriculture Co. Ltd. Changsha China

Developing computer vision–based rice phenotyping techniques is crucial for precision field management and accelerating breeding, thereby continuously advancing rice production. Among phenotyping tasks, distinguishing image components is a key prerequisite for characterizing plant growth and development at the organ scale, enabling deeper insights into eco-physiological processes. However, due to the fine structure of rice organs and complex illumination within the canopy, this task remains highly challenging, underscoring the need for a high-quality training dataset. Such datasets are scarce, both due to a lack of large, representative collections of rice field images and the time-intensive nature of annotation. To address this gap, we established the first comprehensive multi-class rice semantic segmentation dataset, RiceSEG. We gathered nearly 50,000 high-resolution, ground-based images from five major rice-growing countries (China, Japan, India, the Philippines, and Tanzania), encompassing over 6,000 genotypes across all growth stages. From these original images, 3,078 representative samples were selected and annotated with six classes (background, green vegetation, senescent vegetation, panicle, weeds, and duckweed) to form the RiceSEG dataset. Notably, the sub-dataset from China spans all major genotypes and rice-growing environments from the northeast to the south. Both state-of-the-art convolutional neural networks and transformer-based semantic segmentation models were used as baselines. While these models perform reasonably well in segmenting background and green vegetation, they face difficulties during the reproductive stage, when canopy structures are more complex and multiple classes are involved. These findings highlight the importance of our dataset for developing specialized segmentation models for rice and other crops. The RiceSEG dataset is publicly available at ***. © 2025, CC BY.

关键词： Semantic Segmentation

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