咨询与建议

限定检索结果

文献类型

  • 468 篇 期刊文献
  • 319 篇 会议

馆藏范围

  • 787 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 573 篇 工学
    • 311 篇 计算机科学与技术...
    • 273 篇 软件工程
    • 110 篇 信息与通信工程
    • 106 篇 生物工程
    • 83 篇 交通运输工程
    • 69 篇 光学工程
    • 64 篇 电气工程
    • 60 篇 生物医学工程(可授...
    • 57 篇 化学工程与技术
    • 56 篇 控制科学与工程
    • 49 篇 机械工程
    • 41 篇 电子科学与技术(可...
    • 39 篇 建筑学
    • 38 篇 材料科学与工程(可...
    • 37 篇 环境科学与工程(可...
    • 32 篇 土木工程
    • 28 篇 冶金工程
    • 23 篇 仪器科学与技术
  • 358 篇 理学
    • 178 篇 数学
    • 112 篇 生物学
    • 91 篇 物理学
    • 63 篇 统计学(可授理学、...
    • 54 篇 化学
    • 22 篇 系统科学
  • 147 篇 管理学
    • 100 篇 管理科学与工程(可...
    • 52 篇 图书情报与档案管...
    • 51 篇 工商管理
  • 34 篇 医学
    • 28 篇 临床医学
  • 27 篇 法学
    • 25 篇 社会学
  • 26 篇 农学
  • 24 篇 经济学
    • 24 篇 应用经济学
  • 10 篇 教育学
  • 3 篇 文学
  • 2 篇 军事学
  • 1 篇 艺术学

主题

  • 18 篇 deep learning
  • 14 篇 forecasting
  • 13 篇 feature extracti...
  • 12 篇 convolution
  • 11 篇 life cycle
  • 9 篇 neural networks
  • 9 篇 semantics
  • 9 篇 convolutional ne...
  • 8 篇 machine learning
  • 7 篇 covid-19
  • 7 篇 self-supervised ...
  • 7 篇 optimization
  • 7 篇 transportation
  • 6 篇 reinforcement le...
  • 6 篇 semantic segment...
  • 6 篇 image segmentati...
  • 6 篇 graph neural net...
  • 6 篇 computational mo...
  • 6 篇 synthetic apertu...
  • 6 篇 training

机构

  • 46 篇 school of transp...
  • 41 篇 national enginee...
  • 39 篇 national enginee...
  • 30 篇 national enginee...
  • 22 篇 national enginee...
  • 21 篇 henan key labora...
  • 20 篇 peng cheng labor...
  • 20 篇 national enginee...
  • 17 篇 school of comput...
  • 16 篇 national enginee...
  • 15 篇 school of comput...
  • 14 篇 national enginee...
  • 14 篇 school of comput...
  • 13 篇 henan engineerin...
  • 13 篇 national and loc...
  • 13 篇 school of comput...
  • 13 篇 national united ...
  • 11 篇 national enginee...
  • 11 篇 school of transp...
  • 11 篇 college of compu...

作者

  • 46 篇 xia yong
  • 45 篇 zhang yanning
  • 19 篇 wang peng
  • 18 篇 li tianrui
  • 14 篇 xie yutong
  • 13 篇 xi xiaoli
  • 13 篇 liu yugang
  • 13 篇 chen geng
  • 11 篇 nie zuoren
  • 11 篇 chen enhong
  • 11 篇 tian chunwei
  • 11 篇 yang hongtai
  • 11 篇 bin cui
  • 10 篇 liao zehui
  • 10 篇 tong yang
  • 10 篇 sun zhanbo
  • 10 篇 zheng fangfang
  • 10 篇 gong xianzheng
  • 10 篇 zhang jianpeng
  • 10 篇 liu yu

语言

  • 742 篇 英文
  • 29 篇 其他
  • 19 篇 中文
  • 1 篇 德文
  • 1 篇 法文
检索条件"机构=National Engineering Laboratory for Big Data Analysis Technology and Application"
787 条 记 录,以下是741-750 订阅
排序:
Image super-resolution via dynamic network
arXiv
收藏 引用
arXiv 2023年
作者: Tian, Chunwei Zhang, Xuanyu Zhang, Qi Yang, Mingming Ju, Zhaojie School of Software Northwestern Polytechnical University Xi’an710129 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710129 China Research & Development Institute Northwestern Polytechnical University Shenzhen China School of Economics and Management Harbin Institute of Technology at Weihai Weihai264209 China Tencent AI lab Shenzhen China School of Computing University of Portsmouth PortsmouthPO1 3HE United Kingdom
Convolutional neural networks depend on deep network architectures to extract accurate information for image super-resolution. However, obtained information of these convolutional neural networks cannot completely exp... 详细信息
来源: 评论
Model-assisted inference for covariate-specific treatment effects with high-dimensional data
arXiv
收藏 引用
arXiv 2021年
作者: Wu, Peng Tan, Zhiqiang Hu, Wenjie Zhou, Xiao-Hua Beijing International Center for Mathematical Research Peking University Beijing100871 China Department of Statistics Rutgers University 110 Frelinghuysen Road PiscatawayNJ08854 United States Department of Probability and Statistics Peking University Beijing100871 China Department of Biostatistics Beijing International Center for Mathematical Research National Engineering Laboratory of Big Data Analysis and Applied Technology Peking University Beijing100871 China
Covariate-specific treatment effects (CSTEs) represent heterogeneous treatment effects across subpopulations defined by certain selected covariates. In this article, we consider marginal structural models where CSTEs ... 详细信息
来源: 评论
HNF-Netv2 for Brain Tumor Segmentation using multi-modal MR Imaging
arXiv
收藏 引用
arXiv 2022年
作者: Jia, Haozhe Bai, Chao Cai, Weidong Huang, Heng Xia, Yong Research & Development Institute Northwestern Polytechnical University in Shenzhen Shenzhen518057 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi'An710072 China School of Computer Science University of Sydney SydneyNSW2006 Australia Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15261 United States JD Finance America Corporation California CA94043 United States
In our previous work, i.e., HNF-Net, high-resolution feature representation and light-weight non-local self-attention mechanism are exploited for brain tumor segmentation using multi-modal MR imaging. In this paper, w... 详细信息
来源: 评论
H2NF-Net for Brain Tumor Segmentation using Multimodal MR Imaging: 2nd Place Solution to BraTS Challenge 2020 Segmentation Task
arXiv
收藏 引用
arXiv 2020年
作者: Jia, Haozhe Cai, Weidong Huang, Heng Xia, Yong Research & Development Institute Northwestern Polytechnical University in Shenzhen Shenzhen518057 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an710072 China School of Computer Science University of Sydney SydneyNSW2006 Australia Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15261 United States JD Finance America Corporation CaliforniaCA94043 United States
In this paper, we propose a Hybrid High-resolution and Non-local Feature Network (H2NF-Net) to segment brain tumor in multimodal MR images. Our H2NF-Net uses the single and cascaded HNF-Nets to segment different brain... 详细信息
来源: 评论
Novel Hemorrhagic Risk Score in Elderly Patients with Coronary Artery Disease and Gastrointestinal Malignant Tumor Comorbidity:A 10-year Clinical Inpatient data analysis from 2 Medical Centers
收藏 引用
Cardiology Discovery 2021年 第3期1卷 163-172页
作者: Nandi Bao Wanling Wang Huitao Wu Yabin Wang Hebin Che Wenwen Meng Jiaxin Miao Dong Han Fan Yin National Clinical Research Center for Geriatric Diseases The Second Medical Center of Chinese People's Liberation Army General HospitalBeijing 100853China Medical School of Chinese People's Liberation Army General Hospital Beijing 100853China National Engineering Laboratory for Medical Big Data Application Technology The First Medical Center of Chinese People's Liberation Army General HospitalBeijing 100853China Department of Oncology The Second Medical Center of Chinese People's Liberation Army General HospitalBeijing 100853China
Objective:Older patients with comorbidity,such as coronary heart disease(CHD)and malignant gastrointestinal tumors,are at a high risk of bleeding ***,risk prediction models based on risk factor assessment remain *** s... 详细信息
来源: 评论
Reconstructing Missing Modalities in Multi-Modal Endoscopic Ultrasound Via Cross-Modal Feature Replacement Representation
SSRN
收藏 引用
SSRN 2024年
作者: Zheng, Cenyang Gong, Xun Fan, Lin Li, Jiao School of Computing and Artificial Intelligence Southwest Jiaotong University Sichuan Chengdu611756 China Engineering Research Center of Sustainable Urban Intelligent Transportation Ministry of Education Chengdu611756 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu611756 China Manufacturing Industry Chains Collaboration and Information Support Technology Key Laboratory of Sichuan Province Southwest Jiaotong University Chengdu611756 China Department of Gastroenterology The Third People’s Hospital of Chendu Affiliated Hospital of Southwest Jiaotong University Chengdu610031 China
Endoscopic ultrasound (EUS) is the primary diagnostic imaging technique for gastrointestinal stromal tumors. However, accurately identifying these tumors through EUS imaging alone remains challenging, even for experie... 详细信息
来源: 评论
Hierarchical Attention Feature Fusion and Refinement Network for Point Cloud Upsampling
Hierarchical Attention Feature Fusion and Refinement Network...
收藏 引用
IEEE International Conference on Multimedia and Expo (ICME)
作者: Yaori Zhang Shujin Lin Fan Zhou Ruomei Wang National Engineering Research Center of Digital Life School of Computer Science and Engineering Guangdong Provincial Science and Technology Collaborative Innovation Center for Culture and Tourism Sun Yat-sen University Guangzhou China School of Communication and Design Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion Guangdong Provincial Science and Technology Collaborative Innovation Center for Culture and Tourism Sun Yat-sen University Guangzhou China Guangdong Provincial Science and Technology Collaborative Innovation Center for Culture and Tourism National Engineering Research Center of Digital Life School of Computer Science and Engineering Sun Yat-sen University Guangzhou China National Engineering Research Center of Digital Life School of Computer Science and Engineering Sun Yat-sen University Guangzhou China
This paper presents a novel hierarchical attention feature fusion and refinement network designed to address challenges in existing deep learning based point cloud upsampling methods. The network combines self-attenti... 详细信息
来源: 评论
Adaptive Convolutional Neural Network for Image Super-resolution
arXiv
收藏 引用
arXiv 2024年
作者: Tian, Chunwei Zhang, Xuanyu Wang, Tao Zhang, Yongjun Zhu, Qi Lin, Chia-Wen The School of Software Northwestern Polytechnical University Xi’an710129 China The National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710129 China The Yangtze River Delta Research Institute Northwestern Polytechnical University Taicang215400 China The School of Computer Science Northwestern Polytechnical University Xi’an710129 China The College of Computer Science and Technology Guizhou University Guiyang550025 China The School of Artificial Intelligence Nanjing University of Aeronautics and Astronautics Nanjing210016 China The Department of Electrical Engineering The Institute of Communications Engineering National Tsing Hua University Taiwan
Convolutional neural networks can automatically learn features via deep network architectures and given input samples. However, the robustness of obtained models may face challenges in varying scenes. bigger differenc... 详细信息
来源: 评论
PSGR: Pixel-wise sparse graph reasoning for COVID-19 pneumonia segmentation in CT images
arXiv
收藏 引用
arXiv 2021年
作者: Jia, Haozhe Tang, Haoteng Ma, Guixiang Cai, Weidong Huang, Heng Zhan, Liang Xia, Yong National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an710072 China Intel Labs 2111 NE 25th Ave HillsboroOR97124 United States School of Computer Science University of Sydney SydneyNSW2006 Australia Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15261 United States JD Finance America Corporation Mountain View CaliforniaCA94043 United States
Automated and accurate segmentation of the infected regions in computed tomography (CT) images is critical for the prediction of the pathological stage and treatment response of COVID-19. Several deep convolutional ne... 详细信息
来源: 评论
COVID-19大流行期间流感活动呈“断崖式”下降——佩戴口罩、人员流动变化及SARS-CoV-2干扰的作用
收藏 引用
engineering 2023年 第2期21卷 195-202,M0008页
作者: 韩莎莎 张婷 吕岩 赖圣杰 戴佩希 郑建东 杨维中 周晓华 冯录召 Beijing International Center for Mathematical Research Peking UniversityBeijing 100871China Harvard Medical School Harvard UniversityBostonMA 02115USA School of Population Medicine and Public Health Chinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijing 100871China WorldPop School of Geography and Environmental ScienceUniversity of SouthamptonSouthampton SO171BJUK Division for Infectious Diseases Chinese Center for Disease Control and PreventionBeijing 102206China Department of Epidemiology and Biostatistics School of Public HealthPeking UniversityBeijing 100871China National Engineering Laboratory of Big Data Analysis and Applied Technology Peking UniversityBeijing 100871China
一般情况下,每年冬季是季节性流感高发季节,但在当前2019冠状病毒病(COVID-19)大流行期间,全球季节性流感活动呈“断崖式”下降。为应对即将到来的流感季节,亟需弄清这种前所未有的流感低水平流行的原因。本文中,我们探索了一种国家特... 详细信息
来源: 评论