咨询与建议

限定检索结果

文献类型

  • 252 篇 会议
  • 130 篇 期刊文献

馆藏范围

  • 382 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 246 篇 工学
    • 148 篇 计算机科学与技术...
    • 130 篇 软件工程
    • 60 篇 信息与通信工程
    • 53 篇 光学工程
    • 51 篇 生物医学工程(可授...
    • 38 篇 生物工程
    • 35 篇 控制科学与工程
    • 30 篇 机械工程
    • 28 篇 电气工程
    • 26 篇 电子科学与技术(可...
    • 13 篇 仪器科学与技术
    • 11 篇 化学工程与技术
    • 7 篇 交通运输工程
    • 7 篇 安全科学与工程
    • 5 篇 力学(可授工学、理...
    • 5 篇 材料科学与工程(可...
  • 137 篇 理学
    • 82 篇 数学
    • 46 篇 物理学
    • 44 篇 生物学
    • 31 篇 统计学(可授理学、...
    • 13 篇 化学
    • 8 篇 系统科学
  • 39 篇 医学
    • 34 篇 临床医学
    • 27 篇 基础医学(可授医学...
    • 22 篇 药学(可授医学、理...
    • 5 篇 医学技术(可授医学...
  • 33 篇 管理学
    • 21 篇 图书情报与档案管...
    • 16 篇 管理科学与工程(可...
    • 6 篇 工商管理
  • 5 篇 艺术学
    • 5 篇 设计学(可授艺术学...
  • 4 篇 农学
  • 3 篇 法学
  • 3 篇 教育学
  • 2 篇 经济学
  • 2 篇 军事学
  • 1 篇 哲学

主题

  • 40 篇 pattern recognit...
  • 40 篇 image processing
  • 25 篇 image segmentati...
  • 18 篇 feature extracti...
  • 14 篇 computer vision
  • 14 篇 image reconstruc...
  • 13 篇 image recognitio...
  • 12 篇 computer science
  • 12 篇 biomedical imagi...
  • 12 篇 robustness
  • 11 篇 object detection
  • 11 篇 image edge detec...
  • 11 篇 image analysis
  • 10 篇 laboratories
  • 10 篇 shape
  • 9 篇 support vector m...
  • 9 篇 cameras
  • 9 篇 visualization
  • 8 篇 neural networks
  • 8 篇 training

机构

  • 43 篇 institute of ima...
  • 38 篇 institute of ima...
  • 25 篇 institute of ima...
  • 13 篇 department of au...
  • 9 篇 institute of med...
  • 8 篇 department of si...
  • 6 篇 pattern recognit...
  • 6 篇 institute of ima...
  • 5 篇 pattern recognit...
  • 5 篇 the institute of...
  • 5 篇 department for p...
  • 4 篇 department of ul...
  • 4 篇 ieee
  • 4 篇 laboratory of im...
  • 4 篇 institute of ima...
  • 4 篇 pattern recognit...
  • 4 篇 centre for image...
  • 4 篇 department of si...
  • 3 篇 department of au...
  • 3 篇 school of comput...

作者

  • 42 篇 yang jie
  • 18 篇 wang lisheng
  • 18 篇 huang xiaolin
  • 17 篇 jie yang
  • 11 篇 pengfei shi
  • 10 篇 h. bischof
  • 10 篇 yuncai liu
  • 10 篇 chen huai
  • 9 篇 yang yang
  • 9 篇 lisheng wang
  • 9 篇 sergiu nedevschi
  • 8 篇 burkhardt hans
  • 8 篇 liu wei
  • 7 篇 keren fu
  • 6 篇 chen gong
  • 6 篇 w.g. kropatsch
  • 6 篇 bischof horst
  • 6 篇 hong-bin shen
  • 6 篇 ping guo
  • 6 篇 irene y.h. gu

语言

  • 372 篇 英文
  • 6 篇 其他
  • 4 篇 中文
检索条件"机构=Department of Pattern Recognition and Image Processing"
382 条 记 录,以下是101-110 订阅
排序:
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
Learning tubule-sensitive CNNs for pulmonary airway and artery-vein segmentation in CT
arXiv
收藏 引用
arXiv 2020年
作者: Qin, Yulei Zheng, Hao Gu, Yun Huang, Xiaolin Yang, Jie Wang, Lihui Yao, Feng Zhu, Yue-Min Yang, Guang-Zhong Institute of Image Processing and Pattern Recognition Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province School of Computer Science and Technology Guizhou University Guiyang China Department of Thoracic Surgery Shanghai Chest Hospital Shanghai Jiao Tong University Shanghai China Université de Lyon INSA Lyon CREATIS CNRS INSERM UMR 5220 VilleurbanneU1206 France Institute of Medical Robotics School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China
Training convolutional neural networks (CNNs) for segmentation of pulmonary airway, artery, and vein is challenging due to sparse supervisory signals caused by the severe class imbalance between tubular targets and ba... 详细信息
来源: 评论
AIM 2020 Challenge on image Extreme Inpainting  16th
AIM 2020 Challenge on Image Extreme Inpainting
收藏 引用
Workshops held at the 16th European Conference on Computer Vision, ECCV 2020
作者: Ntavelis, Evangelos Romero, Andrés Bigdeli, Siavash Timofte, Radu Hui, Zheng Wang, Xiumei Gao, Xinbo Shin, Chajin Kim, Taeoh Son, Hanbin Lee, Sangyoun Li, Chao Li, Fu He, Dongliang Wen, Shilei Ding, Errui Bai, Mengmeng Li, Shuchen Zeng, Yu Lin, Zhe Yang, Jimei Zhang, Jianming Shechtman, Eli Lu, Huchuan Zeng, Weijian Ni, Haopeng Cai, Yiyang Li, Chenghua Xu, Dejia Wu, Haoning Han, Yu Nadim, Uddin S. M. Jang, Hae Woong Ahmed, Soikat Hasan Yoon, Jungmin Jung, Yong Ju Li, Chu-Tak Liu, Zhi-Song Wang, Li-Wen Siu, Wan-Chi Lun, Daniel P. K. Suin, Maitreya Purohit, Kuldeep Rajagopalan, A.N. Narang, Pratik Mandal, Murari Chauhan, Pranjal Singh Computer Vision Lab ETH Zürich Zürich Switzerland CSEM Neuchâtel Switzerland School of Electronic Engineering Xidian University Xi’an China Image and Video Pattern Recognition Laboratory School of Electrical and Electronic Engineering Yonsei University Seoul Korea Republic of Baidu Inc. Beijing China Beijing China Dalian University of Technology Dalian China Adobe San Jose United States Rensselaer Polytechnic Institute Troy United States Peking University Beijing China Lab Gachon University Seongnam Korea Republic of Centre for Multimedia Signal Processing Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hong Kong China Indian Institute of Technology Madras Chennai India BITS Pilani Pilani India MNIT Jaipur Jaipur India
This paper reviews the AIM 2020 challenge on extreme image inpainting. This report focuses on proposed solutions and results for two different tracks on extreme image inpainting: classical image inpainting and semanti... 详细信息
来源: 评论
Random Fourier features via fast surrogate leverage weighted sampling
arXiv
收藏 引用
arXiv 2019年
作者: Liu, Fanghui Huang, Xiaolin Chen, Yudong Yang, Jie Suykens, Johan A.K. Department of Electrical Engineering [ESAT-STADIUS KU Leuven Belgium Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Institute of Medical Robotics Shanghai Jiao Tong University China School of Operations Research and Information Engineering Cornell University United States
In this paper, we propose a fast surrogate leverage weighted sampling strategy to generate refined random Fourier features for kernel approximation. Compared to the current state-of-the-art method that uses the levera... 详细信息
来源: 评论
Local topology preservation for vascular centerline matching using a hybrid mixture model
Local topology preservation for vascular centerline matching...
收藏 引用
IEEE Symposium on Nuclear Science (NSS/MIC)
作者: Siming Bayer Zhiwei Zhai Maddalena Strumia Xiaoguang Tong Ying Gao Marius Staring Berend Stoel Martin Ostermeier Rebecca Fahrig Arya Nabavi Andreas Maier Nishant Ravikumar Pattern Recognition Lab Friedrich-Alexander Universtiy Erlangen Germany Division of Image Processing Leiden University Medical Center Leiden Netherlands Siemens Healthcare GmbH Forchheim Germany Tianjin Huanhu Hospital Tianjin China Siemens Healthineers Ltd Beijing China Department of Neurosurgery Nordstadt Hospital KRH Hannover Germany
Non-rigid registration is essential for a wide range of clinical applications, such as intraoperative image-guidance and postoperative follow-up assessment, and longitudinal image analysis for disease diagnosis and mo... 详细信息
来源: 评论
Sparse Kernel Regression with Coefficient-based `q−regularization
收藏 引用
Journal of Machine Learning Research 2019年 20卷
作者: Shi, Lei Huang, Xiaolin Feng, Yunlong Suykens, Johan A.K. Shanghai Key Laboratory for Contemporary Applied Mathematics School of Mathematical Sciences Fudan University Shanghai China Institute of Image Processing and Pattern Recognition Institute of Medical Robotics Shanghai Jiao Tong University MOE Key Laboratory of System Control and Information Processing Shanghai China Department of Mathematics and Statistics State University of New York at Albany New York United States Department of Electrical Engineering ESAT-STADIUS KU Leuven Kasteelpark Arenberg 10 LeuvenB-3001 Belgium
In this paper, we consider the `q−regularized kernel regression with 0 q−penalty term over a linear span of features generated by a kernel function. We study the asymptotic behavior of the algorithm under the framewor... 详细信息
来源: 评论
An improved convex programming model for the inverse problem in intensity-modulated radiation therapy
收藏 引用
International Journal of Performability Engineering 2018年 第5期14卷 871-884页
作者: Lan, Yihua Zhang, Xingang Zhang, Jianyang Wang, Yang Hung, Chih-Cheng School of Computer and Information Technology Nanyang Normal University Nanyang473061 China Institute of Image Processing and Pattern Recognition Nanyang Normal University Nanyang473061 China Radiology Department Central Hospital of Nanyang Nanyang473061 China Laboratory for Machine Vision and Security Research College of Computing and Software Engineering Kennesaw State University - Marietta Campus 1100 South Marietta Parkway MariettaGA30067-2896 United States
Intensity modulated radiation therapy technology (IMRT) is one of the main approaches in cancer treatment because it can guarantee the killing of cancer cells while optimally protecting normal tissue from complication... 详细信息
来源: 评论
NCEM: Network structural similarity metric-based clustering for noisy cryo-EM single particle images
NCEM: Network structural similarity metric-based clustering ...
收藏 引用
Chinese Automation Congress
作者: Yin Shuo Biao Zhang Hong-Bin Shen Yang Yang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Department of Computer Science Shanghai Jiao Tong University Shanghai China
Cryo-EM single particle image reconstruction is currently a powerful technique for revealing the structure of biomacromolecules. Compared to traditional structural biology techniques like X-Ray, it requires fewer rest... 详细信息
来源: 评论
REFUGE2 CHALLENGE: A TREASURE TROVE FOR MULTI-DIMENSION ANALYSIS AND EVALUATION IN GLAUCOMA SCREENING
arXiv
收藏 引用
arXiv 2022年
作者: Fang, Huihui Li, Fei Wu, Junde Fu, Huazhu Sun, Xu Son, Jaemin Yu, Shuang Zhang, Menglu Yuan, Chenglang Bian, Cheng Lei, Baiying Zhao, Benjian Xu, Xinxing Li, Shaohua Fumero, Francisco Sigut, José Almubarak, Haidar Bazi, Yakoub Guo, Yuanhao Zhou, Yating Baid, Ujjwal Innani, Shubham Guo, Tianjiao Yang, Jie Orlando, José Ignacio Bogunović, Hrvoje Zhang, Xiulan Xu, Yanwu The REFUGE2 Challenge Australia State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-Sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China Intelligent Healthcare Unit Baidu Inc. Beijing China The Institute of High Performance Computing Agency for Science Technology and Research Singapore Yatiris Group PLADEMA Institute CONICET UNICEN Tandil Argentina Christian Doppler Lab for Artificial Intelligence in Retina Department of Ophthalmology and Optometry Medical University of Vienna Vienna Austria VUNO Inc Seoul Korea Republic of Tencent HealthCare Tencent Shenzhen China Computer Vision Institute College of Computer Science and Software Engineering of Shenzhen University Shenzhen China School of Biomedical Engineering Health Science Center Shenzhen University China Xiaohe Healthcare ByteDance Guangdong Guangzhou510000 China School of Biomedical Engineering Shenzhen University China College of Computer Science & Software Engineering Shenzhen University China Department of Computer Science and Systems Engineering Universidad de La Laguna Spain Saudi Electronic University Saudi Arabia King Saud University Saudi Arabia Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China SGGS Institute of Engineering and Technology India Institute of Medical Robotics Shanghai Jiao Tong University China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China
With the rapid development of artificial intelligence (AI) in medical image processing, deep learning in color fundus photography (CFP) analysis is also evolving. Although there are some open-source, labeled datasets ... 详细信息
来源: 评论
Overexposure correction by mixed one-bit compressive sensing for C-Arm CT  1
收藏 引用
Workshops on image processing for the medicine, 2017
作者: Huang, Xiaolin Xia, Yan Huang, Yixing Hornegger, Joachim Maier, Andreas Pattern Recognition Lab Friedrich-Alexander-University Erlangen-Nürnberg Germany Department of Radiology Stanford University United States Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China
This paper proposes a novel method to deal with overexposure for C-arm CT reconstruction. The proposed method is based on recent progress of one bit compressive sensing (1bit-CS), which is to recover sparse signals fr... 详细信息
来源: 评论