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检索条件"机构=Renmin University of China and Key Laboratory of Data Engineering and Knowledge Engineering"
10155 条 记 录,以下是121-130 订阅
排序:
Decentralized Unlearning for Trustworthy AI-Generated Content (AIGC) Services
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IEEE Network 2025年 第3期39卷 285-292页
作者: Lin, Yijing Du, Hongyang Gao, Zhipeng Yao, Jing Jiang, Bingting Niyato, Dusit Li, Ruidong Zhang, Ping Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China The University of Hong Kong Department of Electrical and Electronic Engineering Pokfulam Hong Kong Central South University School of Computer Science and Engineering Changsha410083 China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China Nanyang Technological University College of Computing and Data Science Jurong West 639798 Singapore Kanazawa University Institute of Science and Engineering Kanazawa920-1192 Japan
The widespread adoption of AI-Generated Content (AIGC) has captured remarkable interests from academia and industry. However, this advancement brings forth challenges in data ownership, as emphasized by the General Da... 详细信息
来源: 评论
Simulation study on stratification and homogeneous combustion of an H2O2-ethanol/gasoline combined injection engine  5
Simulation study on stratification and homogeneous combustio...
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5th International Conference on Mechanical engineering and Materials, ICMEM 2024
作者: Sun, Ping Zhang, Jufang Yu, Xiumin Li, Decheng College of Automotive Engineering Jilin University Changchun130022 China State Key Laboratory of Automotive Simulation and Control Jilin University Changchun130022 China State Key Laboratory of Automotive Simulation and Control Jilin University Renmin Street 5988 Changchun130022 China
Due to the imperfect fuel characteristics, the specific fuel consumption of ethanol fuel was larger than that of gasoline, which limited the application of ethanol fuel in the engine field. H2O2 is a strong activity a... 详细信息
来源: 评论
Detection and interpretation of the time-varying seasonal signals in china with multi-geodetic measurements
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Geodesy and Geodynamics 2025年 第1期16卷 42-54页
作者: Liansheng Deng Yugang Xiao Qusen Chen Wei Peng Zhao Li Hua Chen Zhiwen Wu School of Electrical and Electronic Information Engineering Hubei Polytechnic UniversityHuangshi 435003China Hubei Luojia Laboratory GNSS Research CenterWuhan UniversityWuhan 430079China Changjiang Spatial Information Technology Engineering Co. Ltd.Wuhan 430010China Key Laboratory of Spatial Data Mining&Information Sharing of the Ministry of Education Fuzhou UniversityFuzhou 350108China School of Geodesy and Geomatics Wuhan UniversityWuhan 430079China The First Surveying and Mapping Institute of Hunan Province Changsha 410114China
The time-varying periodic variations in Global Navigation Satellite System(GNSS)stations affect the reliable time series analysis and appropriate geophysical *** this study,we apply the singular spectrum analysis(SSA)... 详细信息
来源: 评论
A Novel Spatiotemporal Correlation Anomaly Detection Method Based on Time-Frequency-Domain Feature Fusion and a Dynamic Graph Neural Network in Wireless Sensor Network
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IEEE Sensors Journal 2025年 第9期25卷 15548-15563页
作者: Ye, Miao Jiang, Zhibang Xue, Xingsi Li, Xingwang Wen, Peng Wang, Yong School of Information and Communication Guilin University of Electronic Technology Guilin541004 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fujian Fuzhou350118 China School of Physics and Electronic Information Engineering Henan Polytechnic University Jiaozuo454099 China
Attention-based transformers have played an important role in wireless sensor network (WSN) timing anomaly detection due to their ability to capture long-term dependencies. However, there are several issues that must ... 详细信息
来源: 评论
PyionNet: Pyramid Progressive Cross-Fusion Network for Joint Classification of Hyperspectral and LiDAR data
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 12042-12058页
作者: Pan, Haizhu Zhang, Quanxiu Ge, Haimiao Liu, Moqi Shi, Cuiping Qiqihar University College of Computer and Control Engineering Qiqihar161000 China Qiqihar University Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar161000 China Xi'an Jiaotong University School of Information and Communications Engineering Shanxi Xi'an710049 China Huzhou University College of Information Engineering Huzhou313000 China
Joint hyperspectral (HS) and Light Detection and Ranging (LiDAR) data for land cover classification have received widespread attention. Nevertheless, existing methods often struggle with multi-scale feature extraction... 详细信息
来源: 评论
SSMamba: Superpixel Segmentation With Mamba
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IEEE Signal Processing Letters 2025年 32卷 1715-1719页
作者: Jia, Xiaohong Li, Yonghui Jiao, Jianjun Zhao, Yao Xia, Zhiwei Lanzhou Jiaotong University School of Electronic and Information Engineering Lanzhou730070 China Beijing Jiaotong University Key Laboratory of Big Data and Artiffcial Intelligence in Transportation Ministry of Education Beijing100044 China Beijing Jiaotong University Institute of Information Science Beijing100044 China
Deep convolutional networks have achieved remarkable success in superpixel segmentation. However, they only focus on local features ignoring global attributes. The visual Mamba demonstrates an exceptional capability t... 详细信息
来源: 评论
SlagNet: A Real-Time Slag Segmentation Model Based on Context and Edge Fusion  16th
SlagNet: A Real-Time Slag Segmentation Model Based on Conte...
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16th International Conference on Modelling, Identification and Control, ICMIC 2024
作者: Liu, Kecheng Li, Jiangyun Yuan, Li School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Beijing100083 China
In the process of iron and steel smelting, steel slag is inevitably produced as a byproduct. Accurately identifying steel slag is a prerequisite for controlling the content of steel slag. Conventional vision-based ste... 详细信息
来源: 评论
Prediction of Rolling Force in Hot Rolling Process Based on Rollformer Model  16th
Prediction of Rolling Force in Hot Rolling Process Based on ...
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16th International Conference on Modelling, Identification and Control, ICMIC 2024
作者: Li, Qing Jiang, Pengyuan Yuan, Li School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Beijing100083 China
In the steel manufacturing industry, the precise forecasting of rolling forces in the hot rolling process is vital for enhancing production efficiency and ensuring product quality. Traditional forecasting methods exhi... 详细信息
来源: 评论
Semantic Scene Completion via Semantic-Aware Guidance and Interactive Refinement Transformer
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IEEE Transactions on Circuits and Systems for Video Technology 2025年 第5期35卷 4212-4225页
作者: Xiao, Haihong Kang, Wenxiong Liu, Hao Li, Yuqiong He, Ying South China University of Technology School of Automation Science and Engineering Guangzhou510641 China South China University of Technology School of Automation Science and Engineering School of Future Technology Guangzhou510641 China Pazhou Laboratory Guangzhou510335 China Nanyang Technological University College of Computing and Data Science Jurong West 639798 Singapore Institute of Mechanics Chinese Academy of Sciences Key Laboratory for Mechanics in Fluid Solid Coupling Systems Beijing100190 China
Predicting per-voxel occupancy status and corresponding semantic labels in 3D scenes is pivotal to 3D intelligent perception in autonomous driving. In this paper, we propose a novel semantic scene completion framework... 详细信息
来源: 评论
Segregation behaviors in{101^(-)1}compressive twin boundaries of Mg-RE alloy under deformation at room temperature
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Journal of Magnesium and Alloys 2025年 第1期13卷 330-337页
作者: Yujie Cui Lili Guo Yunwei Gui Kenta Aoyagi Haotian Tong Qinqin Wei Fangzhou Liu Yuichiro Hayasaka Akihiko Chiba Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology BeijingBeijing 100083China Key Laboratory for Advanced Materials Processing(MOE) University of Science and Technology BeijingBeijing 100083China Beijing Laboratory of Metallic Materials and Processing for Modern Transportation Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China School of Materials Science and Engineering University of Science and Technology BeijingBeijing 100083China Institute for Materials Research Tohoku University2-1-1 KatahiraAoba-kuSendaiMiyagi 980-8577Japan Department of Materials Science and Engineering Jilin University5988 Renmin StreetChangchunJilin 130025China School of Materials Science and Engineering Wuhan University of TechnologyWuhan 430070China The Electron Microscopy Center Tohoku UniversitySendai 980-8577Japan
Solute atoms and precipitates significantly influence the mechanical properties of Mg *** studies have mainly focused on the segregation behaviors of Mg alloys after *** this study,we investigated the segregation beha... 详细信息
来源: 评论