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30th International Symposium on Micro-NanoMechatronics and Human Science, MHS 2019

作者： Zhang, Mengshi Huang, Jian Cao, Yu Zhang, Hai-Tao Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781728126746

Pneumatic Muscles (PMs) - driven exoskeleton has a promising prospect in the field of rehabilitation and assistance, because of the PMs intrinsic features of compliance and high force-to-weight ratio. However, the precise control of PMs-driven exoskeleton still remains a challenging problem due to the hysteresis, time-varying parameters of PMs and complexity of the mechanism. To solve this problem, this paper presents a super twisting controller (STC), essentially a second-order sliding mode control, to realize the human gait tracking control of lower limb exoskeleton. As a result, the disturbances and uncertainties of the system can be handled, and the chattering caused by the traditional sliding mode control (SMC) could be eliminated. The stability of the closed-loop system is ensured according to the Lyapunov theorem. In addition, we conduct experiments in real exoskeleton system and the results illustrate the validity of the super twisting algorithm. Pneumatic Muscles (PMs) - driven exoskeleton has a promising prospect in the field of rehabilitation and assistance, because of the PMs' intrinsic features of compliance and high force-to-weight ratio. However, the precise control of PMs-driven exoskeleton still remains a challenging problem due to the hysteresis, time-varying parameters of PMs and complexity of the mechanism. To solve this problem, this paper presents a super twisting controller (STC), essentially a second-order sliding mode control, to realize the human gait tracking control of lower limb exoskeleton. As a result, the disturbances and uncertainties of the system can be handled, and the chattering caused by the traditional sliding mode control (SMC) could be eliminated. The stability of the closed-loop system is ensured according to the Lyapunov theorem. In addition, we conduct experiments in real exoskeleton system and the results illustrate the validity of the super twisting algorithm.. © 2019 IEEE.

关键词： Sliding mode control

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Enhancing Resilience of Microgrid-Integrated Power Systems in Disaster Events Using Reinforcement Learning 1

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Chinese intelligent Automation Conference, CIAC 2023

作者： Zha, Zhongyi Wang, Bo Liu, Lei Fan, Huijin Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Artificial Intelligence and Automation School Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789819961870

ISBN: (纸本)9789819961863

Enhancing the resilience of power systems has become increasingly important to mitigate the negative impact of risk attacks. Integrating microgrids, which are small-scale power grids that can operate independently or in conjunction with the main grid, has emerged as an effective energy source for emergency situations and can avoid power outages. Typhoons, which are inevitable and relatively easy to predict risk attacks, have become one of the contexts to examine power system resilience. In this paper, we propose a reinforcement learning algorithm that combines graph theory knowledge to make decisions for optimizing power system resilience with microgrids under the Typhoon event. The algorithm effectively utilizes graph theory knowledge and reduces the number of decisions required in the optimization process. Numerical experimental results show that compared to traditional methods, the reinforcement learning algorithm can more effectively respond to typhoon changes, achieve flexible economic control, and enhance the resilience of power systems with microgrids. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Numerical methods

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Lightweight Human Pose Estimation Using Loss Weighted by Target Heatmap 26th

Lightweight Human Pose Estimation Using Loss Weighted by Ta...

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26th International Conference on Pattern Recognition, ICPR 2022

作者： Li, Shiqi Xiang, Xiang 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

ISBN: (纸本)9783031376597

Recent research on human pose estimation exploits complex structures to improve performance on benchmark datasets, ignoring the resource overhead and inference speed when the model is actually deployed. In this paper, we lighten the computation cost and parameters of the deconvolution head network in SimpleBaseline and introduce an attention mechanism that utilizes original, inter-level, and intra-level information to intensify the accuracy. Additionally, we propose a novel loss function called heatmap weighting loss, which generates weights for each pixel on the heatmap that makes the model more focused on keypoints. Experiments demonstrate our method achieves a balance between performance, resource volume, and inference speed. Specifically, our method can achieve 65.3 AP score on COCO test-dev, while the inference speed is 55 FPS and 18 FPS on the mobile GPU and CPU, respectively. © 2023, Springer Nature Switzerland AG.

关键词： Benchmarking

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A three-dimensional transrectal ultrasound imaging system

A three-dimensional transrectal ultrasound imaging system

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

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

ISBN: (纸本)9780769546230

A three dimensional transrectal ultrasound imaging system has been developed. The proposed system is aimed at monitoring for the prostate and providing three-dimensional ultrasound image for prostate biopsy and therapy. The device contains mechanical device and control circuit for the rotation of the probe. In addition, a two dimensional ultrasound machine for 2D ultrasound imaging is used and the software system for the reconstruction of three-dimensional ultrasound image based on PC is developed. Experiments are performed in phantom to validate our prototype. The 3D scan of the agar phantom produces minimal geometric distortion. In the future, our system will be tested on patients. © 2011 IEEE.

关键词： Phantoms

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An Improved Reinforcement Learning for Security-Constrained Economic Dispatch of Battery Energy Storage in Microgrids 1

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2nd International Conference on Neural Computing for Advanced Applications, NCAA 2021

作者： Zha, Zhongyi Wang, Bo Fan, Huijin Liu, Lei Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Artificial Intelligence and Automation School Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789811651885

ISBN: (纸本)9789811651878

Battery energy storage systems are widely used in microgrids integrated with volatile energy resources for their ability in peak load shifting. Security constrained economic dispatch over the system’s lifecycle is a constrained multi-period stochastic optimization problem, which is intractable. We propose an improved actor-critic-based reinforcement learning combined with a protection layer security control method for this issue, where the distributional critic net is applied to estimate the expected total reward value of a period more accurately, and the policy net with a mask action layer is used to make secure and real-time decision. Additionally, we propose a protection layer to assist the policy net as a secondary control to prevent the unsafe state of microgrids due to the trial-and-error learning of reinforcement learning. Numerical test results show the proposed algorithm can perform better than the conventional economic dispatch and other reinforcement learning algorithms while guaranteeing safe operation. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Renewable energy resources

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A change detection algorithm based on object feature for SAR image

A change detection algorithm based on object feature for SAR...

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

作者： Zhang, Xiaohua Li, Hongfeng Jiao, Licheng Institution of Intelligent Information Processing Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an 710071 China

ISBN: (纸本)9781424427314

In the detection of change objects of SAR images, regard to the images containing high intensity noise, traditional methods will produce a considerable false alarm. This paper presents a new method of change detection based on directional information. Direction measure is proposed to suppress noises and brighten object contours. Then region blocks which contain changing objects are extracted according to the difference map of direction measure. Finally, changed objects can be obtained using the OTSU threshold method for each region block. The experimental results on SAR images demonstrate the efficiency and accuracy of the proposed method. ©2009 IEEE.

关键词： Synthetic aperture radar

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Classification based nonlocal means despeckling for SAR image

Classification based nonlocal means despeckling for SAR imag...

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

作者： Zhong, Hua Xu, Jingjing Jiao, Licheng Institution of Intelligent Information Processing Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

The nonlocal (NL) means filter as a recent denoising approach has demonstrated its empirical merit for additive Gaussian noise. In this paper, a new nonlocal means despeckling method for synthetic aperture radar (SAR) image is proposed, which is adapted to the multiplicative model of speckle noise. The proposed method still uses Euclidean distance based similarity measure but adopting a strategy of pixel classification, which can effectively reduce the influence of the multiplicative speckle model and improve the effectiveness in searching of similar patches, thus contributes to the final results. By this strategy, image pixels are first classified into different classes such as point, line, edge, etc., and then different smooth parameters of nonlocal means filter are used according to the class information. In addition, a searching method for rotation-invariant similar patches is designed through the use of directional information. We validate the proposed method on real synthetic aperture radar (SAR) images and confirm the excellent despeckling performance through comparisons with other classical despeckling methods, such the Enhanced Lee filter, Enhanced Gamma MAP filter, wavelet thresholding, as well as original NL mean filter. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image classification

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A multiobjective immune clustering ensemble technique applied to unsupervised SAR image segmentation 10

A multiobjective immune clustering ensemble technique applie...

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ACM International Conference on image and Video Retrieval, ACM-CIVR 2010

作者： Liu, Ruochen Zhang, Wei Jiao, Licheng Liu, Fang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

ISBN: (纸本)9781450301176

In the past few years, multiobjective clustering has been one of the most successful techniques in the field of computer vision and data clustering. This paper proposes a novel unsupervised approach for synthetic aperture radar (SAR) image segmentation, namely, multiobjective immune clustering ensemble technique (MICET). The new technique first divides the image into several regions, and a certain number of pixels are picked out from these regions to form the clustering dataset. Second, artificial immune system (AIS) and multiobjective optimization (MOO) are introduced to generate multiple clustering results, which are then combined together for the following ensemble process. Multiple runs of the multiob-jective clustering method with different randomly selected image features are performed to ensure high quality components as well as necessary diversity for an efficient ensemble. Finally, each datum is assigned to one cluster according to the relationship with the clustering dataset. Experimental results show that interesting segmentation performances on SAR images can be achieved by the proposed technique despite its completely unsupervised nature. Copyright © 2010 ACM.

关键词： Multiobjective optimization

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The trading between virtual mobile operator and wireless service provider in the two-tier Femtocell network

The trading between virtual mobile operator and wireless ser...

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8th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2013

作者： Yang, Fan Yang, Bo Guan, Xinping Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Shanghai Jiao Tong University China

ISBN: (纸本)9783642397004

This paper considers the problem that the virtual mobile operator (VMO) buys services from the wireless service provider (WSP) to serve its users. When faced with poor indoor coverage or at the edge of marcocell, the WSP would ask nearby femto base stations (FBSs) to help serve the VMO. We focus on the interesting questions when the WSP prefers to ask help from FBSs and how WSP, VMO and FBSs adjust their strategies to maximize their profits. A two-stage Stackelberg game is built for the situation when the WSP serve the VMO by itself and a four-stage Stackelberg game is considered when the WSP rents FBSs by offering spectrum bands to FBSs. We firstly define the utility functions of VMO, WSP and FBSs to reflect their satisfaction and cost in participating into the game and then give the analysis based on the backward induction method. Meanwhile, the competition among FBSs when the WSP allocates spectrum bands for FBSs' help is formulated as a non-cooperative spectrum competition game (NSCG) and the existence and uniqueness of the Nash equilibrium in NSCG is proved. Simulation results of the two service modes show the WSP can obtain more profits through renting FBSs in poor coverage areas. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Profitability

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Bagging and Boosting Fine-Tuning for Ensemble Learning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1728-1742页

作者： Zhao, Changming Peng, Ruimin Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074 China and alsowith the ShenzhenHuazhong University of Science and Technology Research Institute Shenzhen 518029 China

Ensemble learning aggregates outputs from multiple base learners for better performance. Bootstrap aggregating (bagging) and boosting are two popular such approaches. They are suitable for integrating unstable base learners with large variance and weak base learners with large bias, respectively, but not base learners with small variance and/or bias, e.g., support vector machine, regularized logistic regression, and ridge regression. This article proposes two novel ensemble-learning-based fine-tuning approaches, boosting fine-tuning (BF) and bagging and boosting fine-tuning (BBF), to fine-tune learners with small variance and/or bias for better performance. BF embeds boosting in a single hidden layer neural network. In each iteration, BF first uses the Newton's method to generate a temporary training set, and then trains a boosting learner on it. BBF combines BF and bagging. It first uses bootstrap to obtain multiple replicas of the training set, and then trains a BF learner on each replica. Extensive experiments on 46 real-world datasets demonstrated that BBF is flexible, robust, and effective, and can fine-tune many popular classifiers to achieve better generalization performance. © 2020 IEEE.

关键词： Support vector machines

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