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检索条件"机构=Key Laboratory of Education Commission for Image Processing and Intelligent Control"
862 条 记 录,以下是351-360 订阅
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Modelling brain based on canonical ensemble with functional MRI: A thermodynamic exploration on neural system
arXiv
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arXiv 2021年
作者: Li, Wei Zhou, Chenxi Yang, Bin Fan, Wenliang Chen, Xi School of Artificial Intelligence and Automation Huazhong University of Science and Technology WuhanHubei430074 China Image Processing and Intelligent Control Key Laboratory of the Education Ministry of China WuhanHubei430074 China Department of Radiology Union Hospital Tongji Medical College Huazhong University of Science and Technology WuhanHubei430074 China
Objective. Modelling is an important way to study the working mechanism of brain. While the characterization and understanding of brain are still inadequate. This study tried to build a model of brain from the perspec... 详细信息
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Probabilistic Robust Parity Relation based Fault Detection Using Biased Minimax Probability Machine ⁎
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IFAC-PapersOnLine 2020年 第2期53卷 646-651页
作者: Yujia Ma Yiming Wan Maiying Zhong Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China College of Electrical Engineering and Automation Shangdong University of Science and Technology Qingdao 266590 China
This paper proposes a probabilistic robust parity relation based approach to fault detection of stochastic linear systems. Instead of assuming exact knowledge of disturbance distribution, the uncertainty of distributi... 详细信息
来源: 评论
FCM-RDpA: TSK fuzzy regression model construction using fuzzy C-means clustering, regularization, droprule, and powerball adabelief
arXiv
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arXiv 2020年
作者: Shi, Zhenhua Wu, Dongrui Guo, Chenfeng Zhao, Changming Cui, Yuqi Wang, Fei-Yue Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China
To effectively optimize Takagi-Sugeno-Kang (TSK) fuzzy systems for regression problems, a mini-batch gradient descent with regularization, DropRule, and AdaBound (MBGD-RDA) algorithm was recently proposed. This paper ... 详细信息
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Mem Brain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction
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Nano-Micro Letters 2018年 第1期10卷 12-19页
作者: Xi Yin Jing Yang Feng Xiao Yang Yang Hong-Bin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Computer Science Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering
Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels,transporters, receptors. Because it is difficult to determinate t... 详细信息
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A polynomial chaos approach to robust H∞ static output-feedback control with bounded truncation error
arXiv
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arXiv 2021年
作者: Wan, Yiming Shen, Dongying E. Lucia, Sergio Findeisen, Rolf Braatz, Richard D. Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan430074 China Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States TU Dortmund University Dortmund44227 Germany Otto-von-Guericke University Magdeburg Magdeburg39106 Germany
This article considers the H∞ static output-feedback control for linear time-invariant uncertain systems with polynomial dependence on probabilistic time-invariant parametric uncertainties. By applying polynomial cha... 详细信息
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Resilient Distributed Predefined Time Secondary control for Cyber-Physical Microgrids
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IET Renewable Power Generation 2025年 第1期19卷
作者: Junfeng Tan Fan Zhang Yanlu Huang Shuai Zhao Hongyu Su China Southern Power Grid Digital Grid Research Institute Co. Ltd. China Southern Power Grid Artificial Intelligence Technology Co. Ltd. Guangzhou China School of Artificial Intelligence and Automation and Technology and also with the Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan China
This paper proposed a resilient distributed predefined-time sliding mode control for islanded AC microgrids with external disturbances caused by noisy circumstances or cyber-attacks. By utilizing the predefined-time c... 详细信息
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Pool-Based Unsupervised Active Learning for Regression Using Iterative Representativeness-Diversity Maximization (iRDM)
arXiv
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arXiv 2020年
作者: Liu, Ziang Jiang, Xue Luo, Hanbin Fang, Weili Liu, Jiajing 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 Technology China School of Civil Engineering and Mechanics Huazhong University of Science and Technology China
Active learning (AL) selects the most beneficial unlabeled samples to label, and hence a better machine learning model can be trained from the same number of labeled samples. Most existing active learning for regressi... 详细信息
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Closer to Pre-trained Network Transfer Better
Closer to Pre-trained Network Transfer Better
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IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)
作者: Siyu Chen Wei Li School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan People’s Republic of China Image Processing and Intelligent Control Key Laboratory Education Ministry of China Wuhan People’s Republic of China
In recent years, Deep Neural Network (DNN) has been widely used in the domain of computer vision, but its further development is restricted because of the lack of train samples. Fine-tuning is one of deep transfer lea... 详细信息
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Transfer Learning for Motor imagery Based Brain-Computer Interfaces: A Complete Pipeline
arXiv
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arXiv 2020年
作者: Wu, Dongrui Jiang, Xue Peng, Ruimin Kong, Wanzeng Huang, Jian Zeng, Zhigang 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 Zhejiang Key Laboratory for Brain-Machine Collaborative Intelligence Hangzhou Dianzi University Hangzhou310018 China
Transfer learning (TL) has been widely used in motor imagery (MI) based brain-computer interfaces (BCIs) to reduce the calibration effort for a new subject, and demonstrated promising performance. While a closed-loop ... 详细信息
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A survey on negative transfer
arXiv
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arXiv 2020年
作者: Zhang, Wen Deng, Lingfei Zhang, Lei Wu, Dongrui the 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 the School of Microelectronics and Communication Engineering Chongqing University Chongqing400044 China
—Transfer learning (TL) utilizes data or knowledge from one or more source domains to facilitate the learning in a target domain. It is particularly useful when the target domain has very few or no labeled data, due ... 详细信息
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