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检索条件"机构=Key Lab of Ministry of Education for Image Processing and Intelligent Control"
887 条 记 录,以下是1-10 订阅
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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 wi... 详细信息
来源: 评论
controllability of neighborhood Corona product networks
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Science China(Information Sciences) 2024年 第12期67卷 327-328页
作者: Bo LIU Xuan LI Qiang ZHANG Junjie HUANG Housheng SU Ministry of Education Key Laboratory for Intelligent Analysis and Security Governance of Ethnic Languages School of Information Engineering Minzu University of China School of Mathematical Sciences Inner Mongolia University 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
controlling networks aims to study the models, structures,and related dynamics of complex networks. The primary problem of controlling networks is to determine whether they are controllable. Nowadays, controllability ...
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Deployment of Heterogeneous Multi-Agent Systems via a PDE Approach
Deployment of Heterogeneous Multi-Agent Systems via a PDE Ap...
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2023 China Automation Congress, CAC 2023
作者: Man, Jingtao Zeng, Zhigang Xiao, Qiang Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education of China Wuhan China
Spatial deployment of large-scale heterogeneous multi-agent systems (HMASs) over desired 2D or 3D curves is investigated in this paper. With assumption that HMASs consist of numerous first-order agents (FOAs) and seco... 详细信息
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Dynamic Color Transform Networks for Wheat Head Detection
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Plant Phenomics 2022年 第1期4卷 395-408页
作者: Chengxin Liu Kewei Wang Hao Lu Zhiguo Cao Key Laboratory of Image Processing and Intelligent Control Ministry of EducationSchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhanChina
Wheat head detection can measure wheat traits such as head density and head *** wheat breeding largely relies on manual observation to detect wheat heads,yielding a tedious and inefficient *** emergence of affordable ... 详细信息
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A Survey on Negative Transfer
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IEEE/CAA Journal of Automatica Sinica 2023年 第2期10卷 305-329页
作者: Wen Zhang Lingfei Deng Lei Zhang Dongrui Wu the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China IEEE the School of Microelectronics and Communication Engineering Chongqing UniversityChongqing 400044China
Transfer learning(TL)utilizes data or knowledge from one or more source domains to facilitate learning in a target *** is particularly useful when the target domain has very few or no labeled data,due to annotation ex... 详细信息
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Transmission-Constrained Consensus of Multiagent Networks
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IEEE Transactions on control of Network Systems 2023年 第3期10卷 1484-1495页
作者: Wang, Xiaotian Su, Housheng Huazhong University of Science and Technology School of Artificial Intelligence and Automation Hubei430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China
This article studies the consensus problem for multiagent systems with transmission constraints. A novel model of multiagent systems is proposed where the information transmissions between agents are disturbed by irre... 详细信息
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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...
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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
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 wi... 详细信息
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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 le... 详细信息
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Bootstrapping Autonomous Lane Changes with Self-supervised Augmented Runs  17th
Bootstrapping Autonomous Lane Changes with Self-supervised ...
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17th European Conference on Computer Vision, ECCV 2022
作者: Xiang, Xiang Key Lab of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China
In this paper, we want to strengthen an autonomous vehicle’s lane-change ability with limited lane changes performed by the autonomous system. In other words, our task is bootstrapping the predictability of lane-chan... 详细信息
来源: 评论
Semisupervised Transfer Boosting (SS-TrBoosting)
IEEE Transactions on Artificial Intelligence
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IEEE Transactions on Artificial Intelligence 2024年 第7期5卷 3431-3444页
作者: Deng, Lingfei Zhao, Changming Du, Zhenbang Xia, Kun Wu, Dongrui 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 and also with Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen 518063 China
Semisupervised domain adaptation (SSDA) aims at training a high-performance model for a target domain using few labeled target data, many unlabeled target data, and plenty of auxiliary data from a source domain. Previ... 详细信息
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