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2021 International Symposium on Micro-NanoMechatronics and Human Science, MHS 2021

作者： Huo, Jun Yang, Bo Ru, Hongge Huang, Jian Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Wuhan430074 China

ISBN: (纸本)9781665407731

It is a positive trend for hemiplegia with wearable robots in rehabilitation training. Recently, wearable Supernumerary Robotic Limb (SRL) is rising to a hot spot. The difficulty in modeling SRL for hemiplegia is how to make the SRL mechanism match the human upper and lower limbs' size and function simultaneously. In this paper, a simplified model of a four Degree of Freedoms (DOFs) universal SRL (USRL) is introduced. Based on workspace similarity, which is evaluated by Jaccard Index (JI), we establish a multi-object optimization (MOO) model. By applying the Particle Swarm Optimization (PSO) algorithm, we have found the optimal SRL mechanism parameters that meet the requirement of the human upper limb and the cane simultaneously. Meanwhile, a few impact factors are discussed briefly in the present proposal. The simulation results show that the USRL has a sound match with the human and could assist the hemiplegia subject as a supplemental limb. © 2021 IEEE.

关键词： Robotics

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An improved segmentation algorithm of color image in complex background based on graph cuts

An improved segmentation algorithm of color image in complex...

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IEEE International Conference on Computer Science and Automation Engineering

作者： Hong, Hanyu Guo, Xiangyun Zhang, Xiuhua Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430074 China

ISBN: (纸本)9781424487257

Recently, it is still difficult to extract interested object from complex background. In this field, interactive image segmentation method has attracted much attention in the vision. In this paper, we propose a new algorithm to segment the interested object from complex background. In the algorithm, we use the improved K-means clustering in the LUV color space to get more accurate classifications of the labeled pixels. Then, build up energy function model and calculate the energy of segmentation properly. Finally, we get the perfect result through graph cuts and denoising algorithm based on connected components. © 2011 IEEE.

关键词： Color

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Steel billet recognition in the heavy rail production line

Steel billet recognition in the heavy rail production line

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2011 International Conference on Automation and Robotics, ICAR 2011

作者： Hong, Hanyu Zhang, Xiuhua Yang, Yijun Yu, Zhejun Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430205 China

ISBN: (纸本)9783642256455

Steel billet recognition is an urgent requirement in the steel industry of heavy rail line. Due to high temperature and complex scene in the rolling line, the recognition at the end of billet is quite different from optical character recognition with simple background and vehicle license plate recognition. In order to solve the problem, this paper presents some new schemes in character location, segmentation and recognition in the complex scene. These proposed algorithms include the location algorithm of multilevel filter based on separability criterion, the segmentation algorithm based on intelligent multi-agent and the recognition algorithm of character features matching combining the template matching. The results show that the proposed algorithms are effective for steel billet character recognition in the complex scene. © 2011 Springer-Verlag.

关键词： Template matching

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Degree of Spiking Neural P Systems Without Delay

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电子学报(英文版) 2012年第3期21卷 419-424页

作者： JIANG Keqin SHI Xiaolong Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China School of Computer and Intormation Anqing Teachers College Anqing 246133 China

Spiking neural P systems are a class of dis- tributed parallel computing models inspired from the way neurons communicate with each other by means of electri- cal impulses (called "spikes"). In this paper, we continue the research of normal forms for spiking neural P systems. Specifically, we prove that the degree of spiking neural P systems without delay can be decreased to two without losing the computational completeness (both in the gener- ating and accepting modes).

关键词：电脉冲神经元膜系统并行计算模型延时分布式

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Tissue P Systems with Look-ahead Mode

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Chinese Journal of Electronics 2014年第1期23卷 81-86页

作者： JIANG Yun SONG Tao ZHANG Zheng School of Computer Science and Information Engineering Chongqing Technology and Business University Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology

Tissue P systems are a class of distributed and parallel computing models inspired from inter-cellular communication and cooperation between cells. In this work, a variant of tissue P system, named tissue P system with look-ahead mode, is discussed for decreasing the inherent non-determinism of tissue P systems and helping implementing tissue P systems on computers. Such systems are proved to be universal by simulating register machine, and they are also proved to be able to efficiently solve computationally hard problems by means of a spacetime tradeoff, which is illustrated with a polynomial solution to 3-coloring problem.

关键词： Tissue P system Look-ahead mode Recursively enumerable language Cell separation 3-Coloring

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Short-Term Residential Load Forecasting via Pooling-Ensemble Model with Smoothing Clustering

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3690-3702页

作者： Xiao, Jiang-Wen Fang, Hongliang Wang, Yan-Wu Huazhong University of Science and Technology Ministry of Education School of Artificial Intelligence and Automation The Key Laboratory of Image Processing and Intelligent Control Wuhan430074 China

Short-term residential load forecasting is essential to demand side response. However, the frequent spikes in the load and the volatile daily load patterns make it difficult to accurately forecast the load. To deal with these problems, this article proposes a smoothing clustering method for daily load clustering and a pooling-ensemble model for one day ahead load forecasting. The whole short-term load forecasting framework in this article contains three steps. Specifically and first, the states of the residents are obtained by clustering the daily load curves with the proposed smoothing clustering method. Second, a weighted mixed Markov model is built to predict the probability distribution of the load state in the next day. Third, multiple predictors in the pooling-ensemble model are selected for different states and the load is forecasted by weighing the results of the multiple predictors based on the predicted states. Results of the case studies and comparison studies on two public datasets verify the advantages of the smoothing clustering method and the pooling-ensemble model. © 2020 IEEE.

关键词： Probability distributions

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A WOA-based algorithm for parameter optimization of support vector regression and its application to condition prognostics 36

A WOA-based algorithm for parameter optimization of support ...

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第36届中国控制会议

作者： LI Sai FANG Huajing School of Automation Key Laboratory of Image Processing and Intelligent ControlMinistry of EducationHuazhong University of Science and Technology

ISBN: (纸本)9781538629185

Condition monitoring is very important for system safety and condition-based *** series prediction capabilities of machine learning like support vector regression(SVR) can be utilized for ***,choosing optimal parameters for SVR is an important step in SVR model design,which heavily affects the performance of ***,a whale optimization algorithm(WOA) based algorithm is proposed for SVR parameters *** proposed algorithm has been evaluated through some benchmark ***,the proposed method with moving window technology is used to condition prognostics of the Tennessee Eastman *** and engineering application show that the SVR-WOA method is effective,by noting that the computation time is shortened in some application scenarios.

关键词： Support vector regression Whale optimization algorithm Parameter optimization Condition prognostics

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Tissue P systems with cell separation: attacking the partition problem

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Science China(Information Sciences) 2011年第2期54卷 293-304页

作者： ZHANG XingYi1, WANG Shuo2, NIU YunYun2 & PAN LinQiang2 1Key Lab of intelligent Computing and Signal processing of Ministry of Education, School of Computer Science and Technology, Anhui University, Hefei 230039, China 2image processing and intelligent control Key Laboratory of Education Ministry of China, Department of control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China 1. Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 China2. Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

Tissue P systems are distributed parallel and non-deterministic computing models in the framework of membrane computing, which are inspired by intercellular communication and cooperation between neurons. Recently, cell separation is introduced into tissue P systems, which enables systems to generate an exponential workspace in a polynomial time. In this work, the computational power of tissue P systems with cell separation is investigated. Specifically, a uniform family of tissue P systems with cell separation is constructed for effciently solving a well-known NP-complete problem, the partition problem.

关键词： membrane computing tissue P system cell separation partition problem

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A battery management system with two-stage equalization 29

A battery management system with two-stage equalization

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第29届中国控制与决策会议

作者： Shengping Hong Jianhua Jiang Xi Li School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent ControlHuazhong University of Science & Technology

ISBN: (纸本)9781509046584

This paper presents a lithium-ion battery pack equalization system and method. The batteries are divided into several groups, which are connected in parallel with the bidirectional DC-DC converters respectively, and the output of DC-DC converters ends are connected in series with each other as a DC bus. The scheme divides equalization of the cells into two stages: intra-group equalization and inter-group equalization, and the two stages are respectively realized by battery time-sharing-access structure and stack energy-sharing structure. Then equalization strategy of the distributed battery energy storage system under two stages is proposed, especially the Single Cell Battery Access Timing Algorithm and MPC Algorithm. The simulation results show that the proposed battery management structure and control strategy can realize fast and accurate SOC equalization.

关键词： Battery management system(BMS) cell equalization battery time-sharing-access structure stack energy-sharing structure Single Cell Battery Access Timing Algorithm MPC Algorithm

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Prompt-guided consistency learning for multi-label classification with incomplete labels

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Neural Networks 2025年

作者： Shouwen Wang Qian Wan Zihan Zhang Zhigang Zeng School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China Key Lab of Image Processing and Intelligent Control Ministry of Education Wuhan 430074 China Independent Researcher Wuhan 430074 China

Addressing insufficient supervision and improving model generalization are essential for multi-label classification with incomplete annotations, i.e. , partial and single positive labels. Recent studies incorporate pseudo-labels to provide additional supervision and enhance model generalization. However, the noise in pseudo-labels generated by the model tends to accumulate, resulting in confirmation bias during training. Self-correction methods, commonly used approaches for mitigating confirmation bias, rely on model predictions but remain susceptible to confirmation bias caused by visual confusion, including both visual ambiguity and similarity. To reduce visual confusion, we propose a prompt-guided consistency learning (PGCL) framework designed for two incomplete labeling settings. Specifically, we introduce an intra-category supervised contrastive loss, which imposes consistency constraints on reliable positive class samples in the feature space of each category, rather than across the feature space of all categories, as in traditional inter-category supervised contrastive loss. Building on this, the distinction between true positive and visual confusion samples for each category is enhanced through label-level contrasting of the same category. Additionally, we develop a class-specific semantic decoupling module that leverages CLIP’s strong vision-language alignment capability, since the proposed contrastive loss requires high-quality label-level representations as contrastive samples. Extensive experimental results on multiple datasets demonstrate that our method can effectively address the problems of two incomplete labeling settings and achieve state-of-the-art performance.

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