咨询与建议

限定检索结果

文献类型

  • 97 篇 会议
  • 55 篇 期刊文献
  • 1 册 图书

馆藏范围

  • 153 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 128 篇 工学
    • 86 篇 计算机科学与技术...
    • 77 篇 软件工程
    • 37 篇 信息与通信工程
    • 30 篇 光学工程
    • 21 篇 电子科学与技术(可...
    • 20 篇 控制科学与工程
    • 14 篇 生物医学工程(可授...
    • 12 篇 生物工程
    • 11 篇 电气工程
    • 10 篇 机械工程
    • 9 篇 航空宇航科学与技...
    • 7 篇 力学(可授工学、理...
    • 7 篇 建筑学
    • 5 篇 仪器科学与技术
    • 5 篇 土木工程
    • 3 篇 化学工程与技术
  • 89 篇 理学
    • 61 篇 数学
    • 34 篇 物理学
    • 17 篇 统计学(可授理学、...
    • 12 篇 生物学
    • 3 篇 化学
    • 3 篇 天文学
    • 3 篇 系统科学
  • 19 篇 管理学
    • 12 篇 图书情报与档案管...
    • 9 篇 管理科学与工程(可...
    • 4 篇 工商管理
  • 5 篇 医学
    • 4 篇 基础医学(可授医学...
    • 4 篇 临床医学
    • 4 篇 药学(可授医学、理...
  • 3 篇 法学
    • 3 篇 社会学
  • 3 篇 军事学
  • 1 篇 经济学
  • 1 篇 文学
  • 1 篇 艺术学

主题

  • 5 篇 image segmentati...
  • 4 篇 motion planning
  • 4 篇 target tracking
  • 4 篇 pattern recognit...
  • 3 篇 image enhancemen...
  • 3 篇 image reconstruc...
  • 3 篇 object recogniti...
  • 2 篇 mixture models
  • 2 篇 knowledge based ...
  • 2 篇 object detection
  • 2 篇 support vector m...
  • 2 篇 compressed sensi...
  • 2 篇 deep learning
  • 2 篇 three-dimensiona...
  • 2 篇 medical imaging
  • 2 篇 pixel
  • 2 篇 pattern matching
  • 2 篇 neural networks
  • 2 篇 face recognition
  • 2 篇 lifting scheme

机构

  • 11 篇 institute of ima...
  • 7 篇 state key lab. o...
  • 5 篇 state key lab. f...
  • 4 篇 key laboratory o...
  • 4 篇 institute for pa...
  • 3 篇 lab. for image p...
  • 3 篇 college of life ...
  • 3 篇 inst. of pattern...
  • 3 篇 state key lab. f...
  • 3 篇 shanghai jiao to...
  • 3 篇 artificial intel...
  • 2 篇 state education ...
  • 2 篇 nanchang hangkon...
  • 2 篇 institute of ima...
  • 2 篇 institute of med...
  • 2 篇 institute of ima...
  • 2 篇 pattern recognit...
  • 2 篇 pattern recognit...
  • 2 篇 national institu...
  • 2 篇 department of im...

作者

  • 9 篇 ding mingyue
  • 9 篇 liu jian
  • 8 篇 cai chao
  • 8 篇 yang jie
  • 7 篇 cao zhiguo
  • 6 篇 maier andreas
  • 6 篇 zhang tianxu
  • 5 篇 zhang tian-xu
  • 5 篇 tian jinwen
  • 5 篇 tian jin-wen
  • 5 篇 zhihua chen
  • 4 篇 jung keechul
  • 4 篇 jie yang
  • 4 篇 wang yuehuan
  • 4 篇 huang yixing
  • 4 篇 zhou chengping
  • 4 篇 guo ping
  • 4 篇 huang xiaolin
  • 3 篇 haxhimusa yll
  • 3 篇 han junghyun

语言

  • 140 篇 英文
  • 12 篇 中文
  • 1 篇 日文
检索条件"机构=Image Processing and Pattern Recognition Lab."
153 条 记 录,以下是151-160 订阅
排序:
A Region-Based Representation of images in MARS
收藏 引用
Journal of VLSI Signal processing Systems for Signal, image, and Video Technology 1998年 第1-2期20卷 137-150页
作者: Servetto, Sergio D. Rui, Yong Ramchandran, Kannan Huang, Thomas S. Beckman Inst. Adv. Sci. and Technol. Univ. Illinois at Urbana-Champaign Urbana IL 61801 United States Universidad Nacional de La Plata Argentina Univ. Illinois at Urbana-Champaign United States Comp. Res. Adv. Applications Group IBM Argentina Argentina Image Formation and Processing Group Beckman Institute UIUC United States Department of Computer Science UNLP Argentina Dept. of Elec. and Comp. Engineering UIUC United States Multimedia Commun. Res. Department Bell Laboratories Murray Hill NJ United States Info. Sciences Research Department AT and T Labs. Florham Park NJ United States Department of Computer Science UIUC United States Southeast University China Tsinghua University China University of Illinois Urbana-Champaign IL United States Image Formation and Processing Group Beckman Inst. Advance Sci. Technol. UIUC United States Vis. Technol. Grp. of Microsoft Res. Redmond WA United States City College of New York United States Columbia University United States AT and T Bell Labs. United States Ctr. for Telecommunications Research Columbia University United States Elec. and Comp. Eng. Department United States Beckman Institute Coordinated Science Laboratory IL United States IEEE Signal Processing Society United States IEEE IMDSP Technical Committee United States IEEE Transactions on Image Proc. United States National Taiwan University Taipei Taiwan Massachusetts Inst. of Technology Cambridge MA United States Department of Electrical Engineering MIT United States School of Electrical Engineering United States Lab. for Info. and Signal Processing Purdue University United States Dept. of Elec. and Comp. Engineering United States Coordinated Science Laboratory United States Image Formation and Processing Group Beckman Inst. Adv. Sci. and Technol. United States MIT Lincoln Laboratory IBM Thomas J. Watson Research Center Rheinishes Landes Museum Bonn Germany Swiss Institutes of Technology Zurich Switzerland Swiss Institutes of Technology Lausanne S
We study the problem of representing images within a multimedia Database Management System (DBMS), in order to support fast retrieval operations without compromising storage efficiency. To achieve this goal, we propos...
来源: 评论
A Recent Survey of Vision Transformers for Medical image Segmentation
arXiv
收藏 引用
arXiv 2023年
作者: Khan, Asifullah Rauf, Zunaira Khan, Abdul Rehman Rathore, Saima Khan, Saddam Hussain Shah, Sahar Farooq, Umair Asif, Hifsa Asif, Aqsa Zahoora, Umme Khalil, Rafi Ullah Qamar, Suleman Asif, Umme Hani Khan, Faiza Babar Majid, Abdul Gwak, Jeonghwan Pattern Recognition Lab Department of Computer & Information Sciences Pakistan Institute of Engineering & Applied Sciences Nilore Islamabad45650 Pakistan Pakistan Institute of Engineering & Applied Sciences Nilore Islamabad45650 Pakistan Center for Mathematical Sciences Pakistan Institute of Engineering & Applied Sciences Nilore Islamabad45650 Pakistan Avid Radio pharmaceuticals PhiladelphiaPA United States Eli Lilly and Company IndianapolisIN United States Swat Pakistan Air University E-9 Islamabad44230 Pakistan Digital Image Processing Lab Department of Computer Science Islamia College Peshawar Pakistan Pakistan Institute of Engineering & Applied Sciences Nilore Islamabad45650 Pakistan Department of Software Korea National University of Transportation Chungju27469 Korea Republic of
Medical image segmentation plays a crucial role in various healthcare applications, enabling accurate diagnosis, treatment planning, and disease monitoring. In recent years, Vision Transformers (ViTs) have emerged as ... 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, lab.led datasets ... 详细信息
来源: 评论