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检索条件"机构=State Key Laboratory of Education Ministry for Image Processing and Intelligent Control"

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Trimmed Data-Driven Evolutionary Optimization Using Selective Surrogate Ensembles 15th

Trimmed Data-Driven Evolutionary Optimization Using Selectiv...

引用

15th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2020

作者： Shan, Yawen Hou, Yongjin Wang, Mengzhen Xu, Fei Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789811613531

Data-driven evolutionary algorithms (DDEAs) have attracted much attention in recent years, due to their effectiveness and advantages in solving expensive and complex optimization problems. In an offline data-driven evolutionary algorithm, no additional information is available to update surrogate models, so we need to ensure the quality of the surrogate models built before optimization. Based on the offline data-driven evolutionary algorithm using selective surrogate ensembles (DDEA-SE), we propose a trimmed bagging based DDEA-SE (TDDEA-SE) to construct a more accurate model pool. To this end, we use trimmed bagging to prune models with large errors calculated by out-of-bag samples, thus improving the accuracy of the selective surrogate ensembles and promoting the optimization. The experimental results on benchmark problems show that the proposed algorithm can strike a balance between diversity and accuracy of models, and its competitiveness on solving offline data-driven optimization problems. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Evolutionary algorithms

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SAR image despeckling based on wavelet kernel transform and gaussian scale mixture model

SAR image despeckling based on wavelet kernel transform and ...

引用

2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Liu, Fan Jiao, Licheng Yang, Shuyuan Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424427314

A new method about SAR image despeckling is proposed in this paper, this method is achieved by combining wavelet kernel transform (WKT) and Gaussian Scale Mixture model (GSM). WKT is a multiscale transform which is based on machine learning model. By analysis the distribution of the coefficients after WKT, these coefficients are similar to Gaussian distribution, and these noised coefficients are distributed as Gaussian too, but are independence with non-noised coefficients. In this paper, we construct the neighbor model based on the coefficients after WKT, and use the Bayes least mean square to despeckle the spots in SAR images, and the model describes the edge distribution of coefficients. We use the proposed method to process the SAR images, and the results demonstrate that this method can obtain better denoising images than Lee filter, wavelet transform etc. ©2009 IEEE.

关键词： Synthetic aperture radar

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Research of method in human detection based on bandelet transform

Research of method in human detection based on bandelet tran...

引用

MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Han, Hong Wu, Xing Jiao, Licheng Yue, Lichuan Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

Based on the geometric flow of images and the second generation bandelet transform, a new feature extraction method was proposed and used to detect human in images. In this paper, bandelet coefficients and their statistical values were extracted as the feature of human images, combined with linear SVM classifier to classify and detect human in images. In the proposed algorithm, some general statistical values of the bandelet coefficients were computed to enhance the classification capacity. The results of human detection experiments indicate that the proposed method can describe human characteristics and improve the performance of classifier effectively. It is very suitable for human detection in images. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Feature extraction

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Thermal Safety Analysis and Dynamic control Strategy for Mode Switching Process of Reversible Solid Oxide Cell System 42

Thermal Safety Analysis and Dynamic Control Strategy for Mod...

引用

42nd Chinese control Conference, CCC 2023

作者： Zhao, Wei Liu, Guoqiang Li, Zexin Li, Xi School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China

ISBN: (纸本)9789887581543

Reversible solid oxide cells (rSOC) can operate in both electrolysis mode and in fuel cell mode with high efficiency and reduced cost using the same device for both functions. When used in dynamic operation with intermittent electrical power sources, rSOC system switches from the fuel cell (SOFC) to electrolyzer (SOEC) and vice versa depending on load and grid peculiarities. This can lead to temperature profiles within the stack that can potentially lead to the failure of the stack and eventually the system. In the present work, a system-level dynamic model of rSOC is established and validated against experimental data. Subsequently, detailed dynamic thermal behavior of stack during the switching between the two modes is analyzed, and a temperature management controller based on Model Predict control method (MPC) is proposed. Gas flow and temperature at the stack inlet are controlled by air flow and bypass valves, avoiding problems associated with temperature overshoot during transient operation. The simulation results show that the temperature controller has the ability to follow fast thermal changes while maintaining thermal safety, which indicates the competitiveness of the controller. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Gas temperature

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Multiple Unmanned Surface Vehicle Coverage control in Dynamic Environments

Multiple Unmanned Surface Vehicle Coverage Control in Dynami...

引用

2023 International Conference on Neuromorphic Computing, ICNC 2023

作者： Chen, Hong He, Dingxin Mao, Huantao Yang, Yong Liu, Zhi-Wei Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China

ISBN: (纸本)9798350316889

This paper investigates the area coverage problem for multiple Unmanned Surface Vehicles (USVs) in dynamic environments. Multiple USVs are employed to execute the coverage task using the Voronoi Partition method for task allocation. Parameter adaptive laws are employed to estimate the parameters of the sensing function and the Voronoi cell centroids for updating the target positions in dynamic environments. Additionally, considering the influence of water surface disturbances, a nonholonomic underactuated model analysis is conducted for the USV under non-full constraints, resulting in a motion strategy for USVs. This enables the multiple USVs to effectively cover the task area. Finally, simulation results are presented to validate the effectiveness of the coverage scheme designed in this paper and the ability of USVs to effectively cover dynamic environments. © 2023 IEEE.

关键词： Unmanned surface vehicles

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Efficient Fabric Defect Detection Algorithm Based on Improved YOLOv5

Efficient Fabric Defect Detection Algorithm Based on Improve...

引用

2023 China Automation Congress, CAC 2023

作者： Tian, LiHua Wang, AoZe Sun, ZhiGang Xiao, Li Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education of China School of Artificial Intelligence and Automation Wuhan China

ISBN: (纸本)9798350303759

In order to address the issues of real-time performance and the low dependency between feature channels in fabric defect detection networks, this paper proposes the ESE-YOLOv5 network based on YOLOv5. Firstly, to address the relative redundancy of the neck detection network feature channels, a relatively lightweight and efficient convolution module is adopted to ensure accuracy while reducing computation and parameter volume. Furthermore, the Efficient Squeeze-Excitation (ESE) module is introduced into the backbone to optimize the dependency of feature channels, which enhances the model's feature extraction capacity and improves detection accuracy. Experimental results show that compared to YOLOv5, the proposed ESE-YOLOv5 model reduces computation and parameter volume while improving accuracy, meeting the needs of fabric defect detection for recognizing fabric defects that have similar characteristics to the background while maintaining real-time performance. © 2023 IEEE.

关键词： Feature extraction

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A method of threaten ordering based on cloud model theory

A method of threaten ordering based on cloud model theory

引用

MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Yu, Xin Wang, Hua Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

Situation assessment (SA) is a complex decision-making process in modern aerial defense system. Threaten ordering (TO) problem is one of the most difficult steps in SA. There are a lot of uncertain factors in TO, and traditional evaluation methods have some disadvantages on algorithm measures. To overcome these disadvantages, a method of TO based on cloud model theory is proposed. Firstly the factors of air-targets threat evaluation are analyzed in this paper. Then the reasoning mechanism base on cloud model is designed. In this step the cloud model is used to depict the attributes of target, the model parameters are defined, and the reasoning rule library is established by using the method of Multiple Attribute Decision Making (MADM). The data of targets were input to the reasoning mechanism, and the threat value was gained. Finally the simulation experiments are given to verify the validity of the method. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Decision making

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Multiobjective Brainstorm Optimization with Diversity Preservation Mechanism for Nonlinear Equation Systems 15th

Multiobjective Brainstorm Optimization with Diversity Preser...

引用

15th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2020

作者： Zhao, Yi Zhu, Zelin Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789811613531

In many fields of engineering and science, it is necessary to solve nonlinear equation systems (NESs). When using multiobjective optimization to solve NESs, there are two problems: 1) how to transform an NES into a multiobjective optimization problem and 2) how to design an algorithm to solve the transformed problems. In this work, we propose a multilayer bi-objective transformation technique, which can transform an NES into a bi-objective optimization problem, and it overcomes the curse of dimensionality and the problem of missing roots caused by the decrease of solutions discernibility in previous transformation techniques. Then, combining the multilayer bi-objective transformation technique, we design a multiobjective brainstorm optimization with a diversity preservation mechanism, which can effectively locate multiple roots of NESs in a single run. Compared with several state-of-art methods on 30 NESs with different features, our approach provides very competitive performance with the highest root ratio and success ratio. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Multiobjective optimization

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A method of COA based on multi-agent evolutionary algorithm

A method of COA based on multi-agent evolutionary algorithm

引用

MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Yu, Xin Wang, Hui Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

Planning detailed military course of action (COA) is very complex and time consuming. In this paper, a method based on multi-agent evolutionary algorithm was presented to solve COA' resource management and scheduling problems. Each individual can be seen as an agent, in order to realize the local perceptivity of agents, the environment is organized as a latticelike structure. Each agent is fixed on a lattice point and it can only interact with its *** agent behaviors which are competition behavior and self-learning behavior are designed. In this work, constraint functions are considered as functions to be optimized like the objectives and then added in competition strategy to deal with the multi-objective aspect of resource-constrained project scheduling problems. This approach avoids the use of a penalty function to deal with constraints. At the same time, the added constraint functions could make the whole algorithm evolving feasible. The simulation results demonstrated that this approach could improve searching ability of this algorithm, and the precision of this method. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Evolutionary algorithms

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An improved watershed-based SAR image segmentation algorithm

An improved watershed-based SAR image segmentation algorithm

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MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Wang, Shuang Zhang, Xiaojing Jiao, Licheng Zhang, Xiangrong Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

The watershed transform is a well-established tool for image segmentation. However, watershed segmentation is often not effective for Synthetic Aperture Radar (SAR) images which are generally corrupted by coherent speckle noise. This paper presents a novel approach for SAR image segmentation using watershed segmentation algorithm combined with Otsu. The aim of this study is to improve the generalization of watershed techniques and to construct a well segmentation of SAR images. Typically, Otsu is used to produce inner mark and external mark. Then we use the mark to modify the gradient image of the SAR image. Additionally, rather than flooding the gradient image, we use the gradient image modified by the mark as input to the watershed algorithm. Experimental results demonstrate the superior performance of the improved watershed-based SAR segmentation. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image segmentation

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