咨询与建议

限定检索结果

文献类型

  • 1,549 篇 期刊文献
  • 1,339 篇 会议
  • 1 册 图书

馆藏范围

  • 2,889 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 1,953 篇 工学
    • 1,359 篇 计算机科学与技术...
    • 1,141 篇 软件工程
    • 459 篇 信息与通信工程
    • 219 篇 生物工程
    • 212 篇 电气工程
    • 211 篇 控制科学与工程
    • 173 篇 电子科学与技术(可...
    • 140 篇 光学工程
    • 106 篇 生物医学工程(可授...
    • 104 篇 机械工程
    • 102 篇 化学工程与技术
    • 84 篇 网络空间安全
    • 77 篇 仪器科学与技术
    • 56 篇 交通运输工程
    • 55 篇 安全科学与工程
    • 52 篇 动力工程及工程热...
    • 47 篇 材料科学与工程(可...
    • 46 篇 土木工程
  • 1,024 篇 理学
    • 500 篇 数学
    • 276 篇 物理学
    • 257 篇 生物学
    • 173 篇 统计学(可授理学、...
    • 94 篇 化学
    • 75 篇 系统科学
  • 519 篇 管理学
    • 278 篇 图书情报与档案管...
    • 251 篇 管理科学与工程(可...
    • 93 篇 工商管理
  • 107 篇 医学
    • 88 篇 临床医学
    • 64 篇 基础医学(可授医学...
  • 87 篇 法学
    • 64 篇 社会学
  • 43 篇 经济学
  • 33 篇 农学
  • 18 篇 教育学
  • 15 篇 军事学
  • 10 篇 文学
  • 3 篇 艺术学

主题

  • 114 篇 semantics
  • 80 篇 feature extracti...
  • 70 篇 deep learning
  • 66 篇 training
  • 64 篇 accuracy
  • 50 篇 federated learni...
  • 47 篇 computational mo...
  • 40 篇 machine learning
  • 36 篇 data mining
  • 36 篇 graph neural net...
  • 34 篇 image segmentati...
  • 34 篇 privacy
  • 33 篇 object detection
  • 32 篇 optimization
  • 30 篇 data models
  • 30 篇 adaptation model...
  • 29 篇 reinforcement le...
  • 28 篇 forecasting
  • 27 篇 neural networks
  • 26 篇 knowledge graph

机构

  • 170 篇 university of ch...
  • 81 篇 cas key lab of n...
  • 74 篇 key laboratory o...
  • 71 篇 shandong provinc...
  • 64 篇 cas key laborato...
  • 52 篇 shandong enginee...
  • 50 篇 network and data...
  • 48 篇 college of compu...
  • 46 篇 school of comput...
  • 45 篇 tianjin key labo...
  • 36 篇 zhejiang lab
  • 35 篇 college of cyber...
  • 34 篇 school of comput...
  • 33 篇 school of cyber ...
  • 31 篇 school of comput...
  • 28 篇 hubei key labora...
  • 28 篇 key lab of infor...
  • 28 篇 national enginee...
  • 28 篇 peng cheng labor...
  • 26 篇 hubei engineerin...

作者

  • 191 篇 cheng xueqi
  • 149 篇 guo jiafeng
  • 48 篇 zhang ruqing
  • 47 篇 fan yixing
  • 44 篇 lan yanyan
  • 43 篇 shen huawei
  • 36 篇 jin xiaolong
  • 31 篇 liu jun
  • 29 篇 pang liang
  • 26 篇 jin hai
  • 25 篇 meng deyu
  • 24 篇 bi keping
  • 22 篇 chen enhong
  • 21 篇 de rijke maarten
  • 21 篇 liu qi
  • 21 篇 wang zhongmin
  • 20 篇 xueqi cheng
  • 20 篇 xu jun
  • 20 篇 li zixuan
  • 19 篇 hu shengshan

语言

  • 2,273 篇 英文
  • 576 篇 其他
  • 43 篇 中文
检索条件"机构=Key Lab of Network Data Science and Technology"
2889 条 记 录,以下是141-150 订阅
排序:
Transformer and Snowball Graph Convolution Learning for Brain Functional network Analysis
Transformer and Snowball Graph Convolution Learning for Brai...
收藏 引用
2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023
作者: Hu, Jinlong Huang, Yangmin Dong, Shoubin South China University of Technology Guangdong Key Lab of Communication and Computer Network School of Computer Science and Engineering Guangzhou China
Advanced deep learning methods, especially graph neural networks (GNNs), are increasingly expected to learn from brain functional network data and predict brain disorders. In this paper, we proposed a novel Transforme... 详细信息
来源: 评论
NumbOD: A Spatial-Frequency Fusion Attack Against Object Detectors  39
NumbOD: A Spatial-Frequency Fusion Attack Against Object Det...
收藏 引用
39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025
作者: Zhou, Ziqi Li, Bowen Song, Yufei Yu, Zhifei Hu, Shengshan Wan, Wei Zhang, Leo Yu Yao, Dezhong Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Computer Science and Technology Huazhong University of Science and Technology China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia
With the advancement of deep learning, object detectors (ODs) with various architectures have achieved significant success in complex scenarios like autonomous driving. Previous adversarial attacks against ODs have be... 详细信息
来源: 评论
Euphemism Detection by Transformers and Relational Graph Attention network  3
Euphemism Detection by Transformers and Relational Graph Att...
收藏 引用
3rd Workshop on Figurative Language Processing, FigLang 2022, as part of EMNLP 2022
作者: Wang, Yuting Liu, Yiyi Zhang, Ruqing Fan, Yixing Guo, Jiafeng CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China
Euphemism is a type of figurative language broadly adopted in social media and daily conversations. People use euphemisms for politeness or to conceal what they are discussing. Euphemism detection is a challenging tas... 详细信息
来源: 评论
A novel network intrusion detection model based on two-phase detection and manually labeling
A novel network intrusion detection model based on two-phase...
收藏 引用
2021 International Conference on Internet of Things and Machine Learning, IoTML 2021
作者: Zhang, Yu Zhou, Yangbo Ma, Xiaowei Tianjin Key Laboratory of Network and Data Security Technology College of Cyber Science Nankai University Tianjin China
network intrusion detection system (NIDS) is a tool that can detect various network attacks by analyzing network traffic. In recent years, traditional machine learning and deep learning methods have been widely used i... 详细信息
来源: 评论
Dual-Threshold Personalized Federated Learning Method Based on Blockchain  4
Dual-Threshold Personalized Federated Learning Method Based ...
收藏 引用
4th International Conference on Blockchain technology and Information Security, ICBCTIS 2024
作者: Liu, Wei Wang, Ying Cui, Wentao She, Wei Tian, Zhao School of Cyber Science and Engineering Zhengzhou University Henan Key Laboratory of Network Cryptography Technology Zhengzhou Key Laboratory of Blockchain and Data Intelligence Zhengzhou China School of Cyber Science and Engineering Zhengzhou University Zhengzhou China School of Cyber Science and Engineering Zhengzhou University SongShan Laboratory Zhengzhou China School of Cyber Science and Engineering Zhengzhou University Zhengzhou Key Laboratory of Blockchain and Data Intelligence Zhengzhou China
Federated learning has emerged as the forefront of research in recent years. However, its distributed framework poses a risk of a single point of failure in data research. Moreover, distinguishing malicious clients in... 详细信息
来源: 评论
A sharding blockchain-based UAV system for search and rescue missions
收藏 引用
Frontiers of Computer science 2025年 第3期19卷 103-118页
作者: Xihan ZHANG Jiashuo ZHANG Jianbo GAO Libin XIA Zhi GUAN Hao HU Zhong CHEN School of Computer Science Peking UniversityBeijing 100871China Peking University Chongqing Research Institute of Big Data Chongqing 401329China National Engineering Research Center for Software Engineering Peking UniversityBeijing 100871China State Key Lab for Novel Software Technology Nanjing UniversityNanjing 210023China
Sharding is a promising technique to tackle the critical weakness of scalability in blockchain-based unmanned aerial vehicle(UAV)search and rescue(SAR)*** breaking up the blockchain network into smaller partitions cal... 详细信息
来源: 评论
Semi-supervised PolSAR image classification method based on contrastive learning  6
Semi-supervised PolSAR image classification method based on ...
收藏 引用
6th International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2023
作者: Hua, Wenqiang Sun, Nan Liu, Lin The Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an Key Laboratory of Big Data and Intelligent Computing School of Computer Science and Technology Xi'an University of Posts and Telecommunications Xi'an China School of Computer Technology Xi'an University of Posts and Telecommunications Xi'an China
Polarimetric synthetic aperture radar (PolSAR) image classification has important application value and a wide range of application scenarios in many fields. Supervised classification methods, which need to use a larg... 详细信息
来源: 评论
Stochastic Block Models for Complex network Analysis: A Survey
收藏 引用
ACM Transactions on Knowledge Discovery from data 2025年 第3期19卷 1-35页
作者: Liu, Xueyan Song, Wenzhuo Musial, Katarzyna Li, Yang Zhao, Xuehua Yang, Bo College of Computer Science and Technology Jilin University Changchun China School of Information Science and Technology Northeast Normal University Changchun China Complex Adaptive Systems Lab Data Science Institute University of Technology Sydney Sydney Australia Aviation University of the Air Force Changchun China School of Digital Media Shenzhen Institute of Information Technology Shenzhen China Key Laboratory of Symbolic Computation and Knowledge Engineer Jilin University Ministry of Education Changchun China
Complex networks enable to represent and characterize the interactions between entities in various complex systems which widely exist in the real world and usually generate vast amounts of data about all the elements,... 详细信息
来源: 评论
Regularization Mixup Adversarial Training: A Defense Strategy for Membership Privacy with Model Availability Assurance  2
Regularization Mixup Adversarial Training: A Defense Strateg...
收藏 引用
2nd International Conference on Big data and Privacy Computing, BDPC 2024
作者: Ding, Zehua Tian, Youliang Wang, Guorong Xiong, Jinbo College of Computer Science and Technology Guizhou University State Key Laboratory of Public Big Data Guiyang China College of Computer and Cyber Security Fujian Normal University Fujian Provincial Key Laboratory of Network Security and Cryptology Fuzhou China
Neural network models face two highly destructive threats in real-world applications: membership inference attacks (MIAs) and adversarial attacks (AAs). One compromises the model's confidentiality, leading to memb... 详细信息
来源: 评论
Learning to Communicate Among Agents for Large-Scale Dynamic Path Planning With Genetic Programming Hyperheuristic
IEEE Transactions on Artificial Intelligence
收藏 引用
IEEE Transactions on Artificial Intelligence 2025年 第5期6卷 1269-1283页
作者: Liao, Xiao-Cheng Hu, Xiao-Min Chen, Xiang-Ling Mei, Yi Jia, Ya-Hui Chen, Wei-Neng Victoria University of Wellington Centre for Data Science and Artificial Intelligence School of Engineering and Computer Science Wellington6140 New Zealand Guangdong University of Technology School of Computer Science and Technology Guangzhou510006 China Hanyang University Department of Electrical and Electronic Engineering Ansan15588 Korea Republic of South China University of Technology School of Future Technology Guangzhou510006 China Pazhou Lab Guangzhou510005 China South China University of Technology School of Computer Science and Engineering State Key Laboratory of Subtropical Building and Urban Science Guangzhou510006 China
Genetic programming hyperheuristic (GPHH) has recently become a promising methodology for large-scale dynamic path planning (LDPP) since it can produce reusable heuristics rather than disposable solutions. However, in... 详细信息
来源: 评论