咨询与建议

限定检索结果

文献类型

  • 1,690 篇 期刊文献
  • 1,569 篇 会议
  • 1 册 图书

馆藏范围

  • 3,260 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 2,138 篇 工学
    • 1,402 篇 计算机科学与技术...
    • 1,202 篇 软件工程
    • 393 篇 信息与通信工程
    • 258 篇 控制科学与工程
    • 230 篇 电气工程
    • 217 篇 化学工程与技术
    • 211 篇 生物工程
    • 181 篇 生物医学工程(可授...
    • 179 篇 机械工程
    • 166 篇 电子科学与技术(可...
    • 148 篇 光学工程
    • 101 篇 仪器科学与技术
    • 88 篇 材料科学与工程(可...
    • 75 篇 动力工程及工程热...
    • 72 篇 建筑学
    • 62 篇 交通运输工程
    • 61 篇 冶金工程
    • 61 篇 土木工程
  • 1,159 篇 理学
    • 647 篇 数学
    • 265 篇 生物学
    • 222 篇 物理学
    • 197 篇 统计学(可授理学、...
    • 160 篇 化学
    • 97 篇 系统科学
  • 597 篇 管理学
    • 352 篇 管理科学与工程(可...
    • 266 篇 图书情报与档案管...
    • 108 篇 工商管理
  • 170 篇 医学
    • 138 篇 临床医学
    • 99 篇 基础医学(可授医学...
    • 66 篇 药学(可授医学、理...
  • 64 篇 法学
  • 62 篇 农学
  • 37 篇 经济学
  • 14 篇 教育学
  • 8 篇 文学
  • 7 篇 艺术学
  • 3 篇 军事学
  • 1 篇 历史学

主题

  • 118 篇 semantics
  • 84 篇 data mining
  • 82 篇 feature extracti...
  • 78 篇 knowledge engine...
  • 77 篇 computer science
  • 73 篇 deep learning
  • 66 篇 training
  • 65 篇 educational inst...
  • 57 篇 laboratories
  • 57 篇 educational tech...
  • 46 篇 neural networks
  • 42 篇 image segmentati...
  • 41 篇 computational mo...
  • 40 篇 predictive model...
  • 40 篇 data models
  • 38 篇 convolution
  • 38 篇 accuracy
  • 37 篇 conferences
  • 37 篇 reinforcement le...
  • 35 篇 visualization

机构

  • 455 篇 college of compu...
  • 271 篇 key laboratory o...
  • 108 篇 school of automa...
  • 90 篇 school of inform...
  • 87 篇 key laboratory o...
  • 85 篇 school of comput...
  • 84 篇 key laboratory o...
  • 55 篇 key laboratory o...
  • 54 篇 shandong provinc...
  • 47 篇 key laboratory o...
  • 46 篇 shandong enginee...
  • 45 篇 school of softwa...
  • 44 篇 college of softw...
  • 40 篇 key laboratory o...
  • 38 篇 key laboratory o...
  • 36 篇 key laboratory o...
  • 33 篇 college of infor...
  • 32 篇 college of compu...
  • 30 篇 key laboratory o...
  • 29 篇 key laboratory o...

作者

  • 41 篇 yang bo
  • 35 篇 liang yanchun
  • 34 篇 sun geng
  • 33 篇 wu xindong
  • 29 篇 niyato dusit
  • 29 篇 du xiaoyong
  • 28 篇 ouyang dantong
  • 28 篇 kaixiang peng
  • 28 篇 chen hong
  • 27 篇 dantong ouyang
  • 27 篇 li xiongfei
  • 26 篇 li ximing
  • 25 篇 ouyang jihong
  • 24 篇 bo yang
  • 23 篇 xindong wu
  • 23 篇 yanchun liang
  • 23 篇 jie dong
  • 22 篇 liu dayou
  • 22 篇 yanheng liu
  • 22 篇 li cuiping

语言

  • 3,021 篇 英文
  • 157 篇 其他
  • 92 篇 中文
检索条件"机构=Key Laboratory of the Ministry of Education for Data Engineering and Knowledge Engineering"
3260 条 记 录,以下是391-400 订阅
排序:
A Federated Learning Based Intelligent Fault Diagnosis Framework for Manufacturing Processes with Intraclass and Interclass Imbalance
SSRN
收藏 引用
SSRN 2024年
作者: Ma, Liang Shi, Fuzhong Peng, Kaixiang Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China
data-based fault diagnosis technology is an important measure to improve the operation safety, stability, and reliability of manufacturing processes, which is a key entry point and innovation power to promote the inte... 详细信息
来源: 评论
A Multi-source Information Fusion Method for Mobile Robot Visual-inertial Navigation  20
A Multi-source Information Fusion Method for Mobile Robot Vi...
收藏 引用
20th IEEE International Conference on Mechatronics and Automation, ICMA 2023
作者: Xu, Changzhen Zhang, Sen Jiang, Kaice Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education 30 Xueyuan Road Haidian District Beijing100083 China University of Science and Technology Beijing School of Automation and Electrical Engineering 30 Xueyuan Road Haidian District Beijing100083 China
Vision sensors have the advantages of low cost and low structural complexity. However, in certain challenging scenarios, such as high dynamic range and high-speed motion, tracking failures and inaccurate positioning m... 详细信息
来源: 评论
Dual-Modeling Decouple Distillation for Unsupervised Anomaly Detection  24
Dual-Modeling Decouple Distillation for Unsupervised Anomaly...
收藏 引用
32nd ACM International Conference on Multimedia, MM 2024
作者: Liu, Xinyue Wang, Jianyuan Leng, Biao Zhang, Shuo School of Computer Science and Engineering Beihang University Beijing China Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Beijing Key Lab of Traffic Data Analysis and Mining School of Computer & Technology Beijing Jiaotong University Beijing China
knowledge distillation based on student-teacher network is one of the mainstream solution paradigms for the challenging unsupervised Anomaly Detection task, utilizing the difference in representation capabilities of t... 详细信息
来源: 评论
A Multi-Objective Evolutionary Machine Learning Method for the Yield Strength Prediction of Strip Steel in Continuous Annealing
A Multi-Objective Evolutionary Machine Learning Method for t...
收藏 引用
IISE Annual Conference and Expo 2024
作者: Liu, Chang Tang, Lixin Zhang, Kainan Guo, Jiajing National Frontiers Science Center for Industrial Intelligence and Systems Optimization North-eastern University Shenyang110819 China Ministry of Education Shenyang110819 China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Shenyang110819 China Liaoning Key Laboratory of Manufacturing System and Logistics Optimization Shenyang110819 China
In the continuous annealing process, the yield strength is the key property index to evaluate the quality of strip steel and guide the production. It is difficult to perform online quality measurement for numerous pro... 详细信息
来源: 评论
Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison
收藏 引用
IEEE/CAA Journal of Automatica Sinica 2023年 第4期10卷 957-968页
作者: Jinhua She Kou Miyamoto Qing-Long Han Min Wu Hiroshi Hashimoto Qing-Guo Wang School of Engineering Tokyo University of TechnologyHachiojiTokyo 192-0982Japan K.Miyamoto is with the Institute of Technology Shimizu CorporationKotoTokyo 135-0044Japan School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia School of Automation China University of GeosciencesWuhan 430074 Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China School of Industrial Technology Advanced Institute of Industrial TechnologyTokyo 140-0011Japan Institute of Artificial Intelligence and Future Networks Beijing Normal UniversityZhuhai 519087 Guangdong Key Lab of AI and Multi-Modal Data Processing Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNUHKBU United International College Zhuhai 519087China
Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state *** paper presents a deep observation on and a comparison between two of those methods:the... 详细信息
来源: 评论
Observation-based sources evolution of non-methane hydrocarbons (NMHCs) in a megacity of China
收藏 引用
Journal of Environmental Sciences 2023年 第2期124卷 794-805页
作者: Yarong Peng Hongli Wang Qian Wang Shengao Jing Jingyu An Yaqin Gao Cheng Huang Rusha Yan Haixia Dai Tiantao Cheng Qiang Zhang Meng Li Jianlin Hu Zhihao Shi Li Li Shengrong Lou Shikang Tao Qinyao Hu Jun Lu Changhong Chen Department of Environmental Science and Engineering Shanghai Key Laboratory of Atmospheric Particle Pollution and PreventionInstitute of Atmospheric SciencesFudan UniversityShanghai 200438China State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex Shanghai Academy of Environmental SciencesShanghai 200233China Department of Atmospheric and Oceanic Sciences Institute of Atmospheric SciencesFudan UniversityShanghai 200438China Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModelingTsinghua UniversityBeijing 100084China Big Data Institute for Carbon Emission and Environmental Pollution Fudan UniversityShanghai 200438China School of Environmental Science and Engineering Nanjing University of Information Science&TechnologyNanjing 210044China
Both concentrations and emissions of many air pollutants have been decreasing due to implement of control measures in China,in contrast to the fact that an increase in emissions of non-methane hydrocarbons(NMHCs)has b... 详细信息
来源: 评论
Distilling Dynamic Spatial Relation Network for Human Pose Estimation  32
Distilling Dynamic Spatial Relation Network for Human Pose E...
收藏 引用
32nd British Machine Vision Conference, BMVC 2021
作者: Wu, Kewei Wang, Tao Xie, Zhao Guo, Dan Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Hefei China School of Computer Science and Information Engineering Hefei University of Technology Hefei China
Human pose estimation is a challenging task that requires the comprehension of the pose structure. This work can refer to spatial relation inference in a pose structure model;how to model the dynamic spatial relation ... 详细信息
来源: 评论
Electronic Medical Record Sharing System Based on Hyperledger Fabric and InterPlanetary File System  2021
Electronic Medical Record Sharing System Based on Hyperledge...
收藏 引用
5th International Conference on Compute and data Analysis, ICCDA 2021
作者: Li, Lei Yue, Zhengxiang Wu, Gongqing Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Hefei China School of Computer Science and Information Engineering Hefei University of Technology Hefei China
Electronic Medical Records (EMR) and other medical data contain important and sensitive privacy information of patients, which provide important basis and reference for their doctors to diagnose and treat them. With t... 详细信息
来源: 评论
NIR-II fluorescence molecular tomography based on transformer encoder architecture
NIR-II fluorescence molecular tomography based on transforme...
收藏 引用
Medical Imaging 2025: Clinical and Biomedical Imaging
作者: Bao, Jie Xiao, Anqi Han, keyi Pei, Ziyu Fu, Lidan Tian, Jie Hu, Zhenhua CAS Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular Imaging Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Engineering Medicine Beihang University Beijing China Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education School of Life Science and Technology Xidian University Xi’an China National Key Laboratory of Kidney Diseases Beijing China
Fluorescence molecular tomography (FMT) is a highly sensitive method for depicting the three-dimensional distribution of fluorescent targets within biological tissues. However, traditional FMT reconstruction can be af... 详细信息
来源: 评论
An Encoder-Based Framework for Privacy-Preserving Machine Learning  24th
An Encoder-Based Framework for Privacy-Preserving Machine L...
收藏 引用
24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024
作者: Wu, Jiayun Ren, Wei Zhang, Xianchao Zheng, Xianghan School of Computer Science China University of Geosciences Wuhan430074 China State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR CASM Beijing China Ministry of Education Chengdu China Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province Jiaxing University Jiaxing China Engineering Research Center of Intelligent Human Health Situation Awareness of Zhejiang Province Jiaxing University Jiaxing China College of Computer and Big Data Fuzhou University Fujian Fuzhou China School of Information and Intelligent Engineering Sanya College Hainan China
As a data-driven science, machine learning requires vast amounts of training data and computational resources. However, for highly privacy-sensitive data, it is crucial to protect the privacy of the data during both t... 详细信息
来源: 评论