咨询与建议

限定检索结果

文献类型

  • 121 篇 会议
  • 94 篇 期刊文献

馆藏范围

  • 215 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 138 篇 工学
    • 93 篇 计算机科学与技术...
    • 77 篇 软件工程
    • 26 篇 生物工程
    • 25 篇 信息与通信工程
    • 19 篇 控制科学与工程
    • 16 篇 光学工程
    • 15 篇 机械工程
    • 12 篇 化学工程与技术
    • 7 篇 生物医学工程(可授...
    • 4 篇 仪器科学与技术
    • 4 篇 电气工程
    • 4 篇 建筑学
    • 4 篇 土木工程
    • 4 篇 交通运输工程
    • 4 篇 安全科学与工程
    • 3 篇 电子科学与技术(可...
    • 2 篇 材料科学与工程(可...
    • 2 篇 动力工程及工程热...
    • 2 篇 船舶与海洋工程
  • 83 篇 理学
    • 30 篇 数学
    • 28 篇 生物学
    • 25 篇 物理学
    • 11 篇 统计学(可授理学、...
    • 9 篇 化学
    • 8 篇 系统科学
  • 48 篇 管理学
    • 27 篇 管理科学与工程(可...
    • 23 篇 图书情报与档案管...
    • 7 篇 工商管理
  • 4 篇 法学
    • 4 篇 社会学
  • 3 篇 医学
  • 3 篇 艺术学
    • 3 篇 设计学(可授艺术学...
  • 1 篇 经济学
  • 1 篇 教育学
  • 1 篇 农学

主题

  • 18 篇 feature extracti...
  • 14 篇 speech recogniti...
  • 13 篇 training
  • 12 篇 pattern recognit...
  • 12 篇 semantics
  • 9 篇 face recognition
  • 6 篇 deep neural netw...
  • 6 篇 hidden markov mo...
  • 6 篇 data mining
  • 6 篇 machine learning
  • 6 篇 image classifica...
  • 6 篇 computer vision
  • 6 篇 character recogn...
  • 5 篇 robustness
  • 5 篇 intelligent syst...
  • 4 篇 support vector m...
  • 4 篇 deep learning
  • 4 篇 image segmentati...
  • 4 篇 convolution
  • 4 篇 vectors

机构

  • 72 篇 pattern recognit...
  • 20 篇 pattern recognit...
  • 16 篇 the pattern reco...
  • 10 篇 guizhou key labo...
  • 9 篇 school of comput...
  • 8 篇 pattern recognit...
  • 6 篇 school of comput...
  • 6 篇 pattern recognit...
  • 5 篇 department of st...
  • 4 篇 university of ch...
  • 4 篇 center for resea...
  • 4 篇 beijing universi...
  • 3 篇 pattern recognit...
  • 3 篇 college of physi...
  • 3 篇 shanghai jiao to...
  • 3 篇 department of st...
  • 3 篇 cas center for e...
  • 3 篇 meituan group
  • 3 篇 key laboratory o...
  • 3 篇 center for resea...

作者

  • 33 篇 guo jun
  • 29 篇 ma zhanyu
  • 29 篇 jun guo
  • 19 篇 gang liu
  • 18 篇 deng weihong
  • 13 篇 honggang zhang
  • 12 篇 liu gang
  • 10 篇 chang dongliang
  • 10 篇 song yi-zhe
  • 9 篇 yang yang
  • 9 篇 li xiaoxu
  • 9 篇 du ruoyi
  • 8 篇 feng fujian
  • 8 篇 liang yihui
  • 8 篇 wang lin
  • 7 篇 zhang honggang
  • 7 篇 wang mei
  • 7 篇 xue jing-hao
  • 6 篇 zhanyu ma
  • 6 篇 wei chen

语言

  • 208 篇 英文
  • 7 篇 中文
  • 2 篇 其他
检索条件"机构=Laboratory of Pattern Recognition and Intelligent System"
215 条 记 录,以下是81-90 订阅
排序:
Mind the gap: Enlarging the domain gap in open set domain adaptation
arXiv
收藏 引用
arXiv 2020年
作者: Chang, Dongliang Sain, Aneeshan Ma, Zhanyu Song, Yi-Zhe Guo, Jun Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China Centre for Vision Speech and Signal Processing University of Surrey London United Kingdom
Unsupervised domain adaptation aims to leverage labeled data from a source domain to learn a classifier for an unlabeled target domain. Among its many variants, open set domain adaptation (OSDA) is perhaps the most ch... 详细信息
来源: 评论
Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non–Contrast CT Images
arXiv
收藏 引用
arXiv 2021年
作者: Liang, Kongming Han, Kai Li, Xiuli Cheng, Xiaoqing Li, Yiming Wang, Yizhou Yu, Yizhou Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China Deepwise AI Lab Beijing China Department of Medical Imaging Jinling Hospital Nanjing University School of Medicine Jiangsu Nanjing China Department of Computer Science and Technology Peking University Beijing China The University of Hong Kong Pokfulam Hong Kong
Quantitative estimation of the acute ischemic infarct is crucial to improve neurological outcomes of the patients with stroke symptoms. Since the density of lesions is subtle and can be confounded by normal physiologi... 详细信息
来源: 评论
Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid Network
arXiv
收藏 引用
arXiv 2022年
作者: Li, Wenjie Li, Juncheng Gao, Guangwei Deng, Weihong Yang, Jian Qi, Guo-Jun Lin, Chia-Wen Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100080 China Intelligent Visual Information Perception Laboratory Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210046 China Key Laboratory of Artificial Intelligence Ministry of Education Shanghai200240 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China School of Communication and Information Engineering Shanghai University Shanghai200444 China School of Computer Science and Technology Nanjing University of Science and Technology Nanjing210094 China Research Center for Industries of the Future the School of Engineering Westlake University Hangzhou310024 China OPPO Research SeattleWA98101 United States Department of Electrical Engineering National Tsing Hua University Hsinchu30013 Taiwan
Lightweight image super-resolution aims to reconstruct high-resolution images from low-resolution images using low computational costs. However, existing methods result in the loss of middle-layer features due to acti... 详细信息
来源: 评论
A concise review of recent few-shot meta-learning methods
arXiv
收藏 引用
arXiv 2020年
作者: Li, Xiaoxu Sun, Zhuo Xue, Jing-Hao Ma, Zhanyu School of Computer and Communication Lanzhou University of Technology China Department of Statistical Science University College London United Kingdom Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications China
Few-shot meta-learning has been recently reviving with expectations to mimic humanity's fast adaption to new concepts based on prior knowledge. In this short communication, we give a concise review on recent repre... 详细信息
来源: 评论
NiuEM: A Nested-iterative Unsupervised Learning Model for Single-particle Cryo-EM Image Processing
NiuEM: A Nested-iterative Unsupervised Learning Model for Si...
收藏 引用
2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020
作者: Hu, Rui Cai, Jiaming Zheng, Wangjie Yang, Yang Shen, Hong-Bin Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Jiao Tong University Department of Bioinformatics and Biostatistics Shanghai200240 China
Cryo-electron microscopy (cryo-EM) has become a mainstream technology for solving spatial structures of biomacromolecules, while the processing of cryo-EM images is a very challenging task. One of the great challenges... 详细信息
来源: 评论
Cross-receptive Focused Inference Network for Lightweight Image Super-Resolution
arXiv
收藏 引用
arXiv 2022年
作者: Li, Wenjie Li, Juncheng Gao, Guangwei Deng, Weihong Zhou, Jiantao Yang, Jian Qi, Guo-Jun The Intelligent Visual Information Perception Laboratory Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210046 China The Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China The School of Communication and Information Engineering Shanghai University Shanghai200444 China Jiangsu Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology Nanjing210094 China The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China The State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science Faculty of Science and Technology University of Macau 999078 China The School of Computer Science and Technology Nanjing University of Science and Technology Nanjing210094 China The Research Center for Industries of the Future The School of Engineering Westlake University Hangzhou310024 China OPPO Research SeattleWA98101 United States
Recently, Transformer-based methods have shown impressive performance in single image super-resolution (SISR) tasks due to the ability of global feature extraction. However, the capabilities of Transformers that need ... 详细信息
来源: 评论
A deeper look at facial expression dataset bias
arXiv
收藏 引用
arXiv 2019年
作者: Li, Shan Deng, Weihong Pattern Recognition and Intelligent System Laboratory School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China
Datasets play an important role in the progress of facial expression recognition algorithms, but they may suffer from obvious biases caused by different cultures and collection conditions. To look deeper into this bia... 详细信息
来源: 评论
The devil is in the channels: Mutual-channel loss for fine-grained image classification
arXiv
收藏 引用
arXiv 2020年
作者: Chang, Dongliang Ding, Yifeng Xie, Jiyang Bhunia, Ayan Kumar Li, Xiaoxu Ma, Zhanyu Wu, Ming Guo, Jun Song, Yi-Zhe Pattern Recognition and Intelligent System Laboratory School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China School of Computer and Communication Lanzhou University of Technology Lanzhou730050 China Centre for Vision Speech and Signal Processing University of Surrey London United Kingdom
The key to solving fine-grained image categorization is finding discriminate and local regions that correspond to subtle visual traits. Great strides have been made, with complex networks designed specifically to lear... 详细信息
来源: 评论
NiuEM: A Nested-iterative Unsupervised Learning Model for Single-particle Cryo-EM Image Processing
NiuEM: A Nested-iterative Unsupervised Learning Model for Si...
收藏 引用
IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
作者: Rui Hu Jiaming Cai Wangjie Zheng Yang Yang Hong-Bin Shen Shanghai Jiao Tong University and Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Jiao Tong University Shanghai China
Cryo-electron microscopy (cryo-EM) has become a mainstream technology for solving spatial structures of biomacromolecules, while the processing of cryo-EM images is a very challenging task. One of the great challenges... 详细信息
来源: 评论
BSNet: Bi-similarity network for few-shot fine-grained image classification
arXiv
收藏 引用
arXiv 2020年
作者: Li, Xiaoxu Wu, Jijie Sun, Zhuo Ma, Zhanyu Cao, Jie Xue, Jing-Hao School of Computer and Communication Lanzhou University of Technology Lanzhou730050 China Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China Department of Statistical Science University College London LondonWC1E 6BT United Kingdom
Few-shot learning for fine-grained image classification has gained recent attention in computer vision. Among the approaches for few-shot learning, due to the simplicity and effectiveness, metric-based methods are fav... 详细信息
来源: 评论