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Knowledge-Data Fusion Based Source-Free Semi-Supervised Domain Adaptation for Seizure Subtype Classification

Knowledge-Data Fusion Based Source-Free Semi-Supervised Doma...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Peng, Ruimin An, Jiayu Wu, Dongrui School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control Wuhan430074 China

ISBN: (纸本)9781665410205

Electroencephalogram (EEG)-based seizure sub-type classification enhances clinical diagnosis efficiency. Source-free semi-supervised domain adaptation (SF-SSDA), which transfers a pre-trained model to a new dataset with no source data and limited labeled target data, can be used for privacy-preserving seizure subtype classification. This paper considers two challenges in SF-SSDA for EEG-based seizure subtype classification: 1) How to effectively fuse both raw EEG data and expert knowledge in classifier design? 2) How to align the source and target domain distributions for SF-SSDA? We propose a Knowledge-Data Fusion based SF-SSDA approach, KDF-MutuaISHOT, for EEG-based seizure subtype classification. In source model training, KDF uses Jensen-Shannon Diver-gence to facilitate mutual learning between a feature-driven Decision Tree-based model and a data-driven Transformer-based model. To adapt KDF to a new target dataset, an SF-SSDA algorithm, MutualSHOT, is developed, which features a consistency-based pseudo-label selection strategy. Experiments on the public TUSZ and CHSZ datasets demonstrated that KDF-MutualSHOT outperformed other supervised and source-free domain adaptation approaches in cross-subject seizure subtype classification. © 2024 IEEE.

关键词： Self-supervised learning

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A new artificial immune network classifier for SAR image

A new artificial immune network classifier for SAR image

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MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Liu, Ruochen Niu, Manchun Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding Institute of Intelligent Information Processing Xidian University Xi'an Shaanxi 710071 China

ISBN: (纸本)9780819478078

Inspired by the idiotypic network theory, a new artificial immune network classifier for SAR image is proposed in this paper. In the proposed algorithm, only one B-cell instead of many B-cells is used to denote a class so as to reduce the scale of network as well as avoid the suppression operation between B-cells;moreover, a new affinity function based on the correct rate is proposed to realize antigen priority based the evaluation strategy. The proposed algorithm has been extensively compared with Fuzzy C-means (FCM), Multiple-Valued Immune Network algorithm (MVIN), and Clonal Selection Algorithm for classifier (CSA) over two SAR images. The result of experiment indicates the superiority of the algorithm over FCM, MVIN and CSA on classification accuracy and robustness. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Synthetic aperture radar

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A new constrained spectral clustering for SAR image segmentation

A new constrained spectral clustering for SAR image segmenta...

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

作者： Zou, Haishuang Zhou, Weida Zhang, Li Wu, Caili Liu, Ruochen Jiao, Licheng Institute of Intelligent Information Processing Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University 710071 China

ISBN: (纸本)9781424427314

Pairwise constraints have been successful to be applied in traditional clustering methods. However, little progress has been made in incorporating them into spectral clustering. In this paper, we propose a new method to combine pairwise constraints with spectral clustering and apply it to SAR image segmentation. Firstly, we learn a distance metric using pairwise constraints. In doing so, an affinity matrix is obtained by the Gaussian function on the learned distance metric. Then we perform the spectral decomposition on the affinity matrix and we get the spectral features of data points. Finally, the constrained k-means is used to cluster spectral features instead of k-means used commonly. We apply the proposed method to synthetic aperture radar (SAR) image segmentation. Experimental results show that it is effective for SAR image segmentation. ©2009 IEEE.

关键词： image segmentation

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Super Twisting control of Passive Gait Training Exoskeleton Driven by Pneumatic Muscles 30

Super Twisting Control of Passive Gait Training Exoskeleton ...

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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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On-line signature verification using wavelet packet

On-line signature verification using wavelet packet

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2011 International Joint Conference on Biometrics, IJCB 2011

作者： Wang, Kaiyue Wang, Yunhong Zhang, Zhaoxiang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Beihang University Beijing 100191 China

ISBN: (纸本)9781457713583

In this paper, we propose a novel approach for on-line signature verification using wavelet packet. Signatures are first normalized and resampled, thus they have the same number of sample points. Then, several types of local features are extracted, so that wavelet transform can be applied on them. After that, we conduct experiments to select the best local features, wavelet bases and wavelet packet settings. Also, experiments are carried out to verify the reliability and efficiency of our approach, which performs better than discrete wavelet transform and competes with the state-of-arts. © 2011 IEEE.

关键词： Discrete wavelet transforms

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Design of a wearable rehabilitation robotic hand actuated by pneumatic artificial muscles

Design of a wearable rehabilitation robotic hand actuated by...

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2009 7th Asian control Conference, ASCC 2009

作者： Kexin, Xing Jian, Huang Qi, Xu Yongji, Wang Key Lab. of Image Processing and Intelligent Control Department of Control Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9788995605691

Intensive task-oriented repetitive physical therapies provided by individualized interaction between the patient and the rehabilitation specialist can improve the hand motor performance of the patient survived from stroke or traumatic brain injury. However, the therapy is time-consuming and expensive. Furthermore, it is difficult to evaluate the result of therapy quantitatively and objectively. The goal of this research is to develop a novel wearable device for robotic assistive hand repetitive therapy. We designed a pneumatic artificial muscle (PAM) driven rehabilitation robotic hand that is wearable and provides assistive forces required for grasping and release movements. The robot has two distinct degrees of freedom at the thumb and the fingers. The embedded sensors are employed to obtain the feedback position and force information for robot control and quantitative evaluation of task performance. To encourage the patients' self-regulation and improve the performance of the task, a PC based Virtual Reality game was developed. In order to realize a compliant and smooth motion, cubic spline functions are adopted in the trajectory planning of metacarpophalangeal joints. To realize the trajectory tracking control, a conventional PID controller was implemented and evaluated. Experiments were performed to confirm the effectiveness of the proposed device and methods. The robot has the potential of providing supplemental at-home therapy in addition to in the clinic treatment. ©2009 ACA.

关键词： Degrees of freedom (mechanics)

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

引用

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...

引用

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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Transmit aperture function for large depth focusing combined with phase coherence imaging for interference suppressing

Transmit aperture function for large depth focusing combined...

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

作者： Xu, Mengling Chen, Yimin Yuchi, Ming 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

Dynamic focus and dynamic aperture applied on both transmit and receive aperture can provide the best possible quality of the B-mode ultrasound image, which is called a "gold standard" image. However, they are implemented only on the receive beam in most medical ultrasound systems because the application of dynamic focus on the transmit beam will reduce the frame rate severely, which has great medical importance especially when tissue motion needs to be considered. Recently, a specific transmit aperture function has been proposed to achieve uniform transmit energy distribution on the axis over a large depth without reducing the frame rate. Although it can maintain the uniformity of the transmit energy on the axis, the energy distribution off the axis of the transmit beam is not satisfactory, meaning a wider main lobe width and higher side lobe levels compared with some general aperture functions such as rectangular and hamming functions. To suppress the interference signals originating from the targets on the side and grating lobes, we processed the received echo signals using the phase coherence imaging method (PCI), which is an adaptive receive aperture weighting technique presented in the recent literatures. Experimental results show that the uniform sensitivity along the axis range has been achieved and image quality on spatial and contrast resolution improved when we use the transmit aperture function combined with PCI. © 2011 IEEE.

关键词： Ultrasonic applications

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