咨询与建议

限定检索结果

文献类型

  • 581 篇 会议
  • 303 篇 期刊文献
  • 1 册 图书

馆藏范围

  • 885 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 609 篇 工学
    • 330 篇 计算机科学与技术...
    • 296 篇 软件工程
    • 197 篇 信息与通信工程
    • 84 篇 生物工程
    • 76 篇 光学工程
    • 76 篇 电子科学与技术(可...
    • 74 篇 控制科学与工程
    • 73 篇 机械工程
    • 73 篇 电气工程
    • 61 篇 生物医学工程(可授...
    • 43 篇 仪器科学与技术
    • 35 篇 化学工程与技术
    • 17 篇 材料科学与工程(可...
    • 16 篇 安全科学与工程
    • 14 篇 土木工程
    • 13 篇 力学(可授工学、理...
    • 13 篇 建筑学
    • 13 篇 交通运输工程
  • 360 篇 理学
    • 187 篇 数学
    • 140 篇 物理学
    • 87 篇 生物学
    • 68 篇 统计学(可授理学、...
    • 34 篇 化学
    • 33 篇 系统科学
  • 93 篇 管理学
    • 59 篇 管理科学与工程(可...
    • 35 篇 图书情报与档案管...
  • 56 篇 医学
    • 52 篇 临床医学
    • 25 篇 基础医学(可授医学...
    • 20 篇 药学(可授医学、理...
  • 14 篇 农学
  • 12 篇 法学
    • 11 篇 社会学
  • 6 篇 经济学
  • 3 篇 教育学
  • 3 篇 军事学
  • 2 篇 艺术学

主题

  • 43 篇 feature extracti...
  • 26 篇 image segmentati...
  • 22 篇 visualization
  • 22 篇 image reconstruc...
  • 21 篇 image coding
  • 19 篇 convolution
  • 17 篇 semantics
  • 17 篇 image quality
  • 17 篇 training
  • 14 篇 image color anal...
  • 13 篇 image communicat...
  • 13 篇 support vector m...
  • 13 篇 deep learning
  • 13 篇 three-dimensiona...
  • 13 篇 psnr
  • 13 篇 encoding
  • 13 篇 robustness
  • 12 篇 video coding
  • 12 篇 image processing
  • 12 篇 estimation

机构

  • 82 篇 institute of ima...
  • 63 篇 moe key lab of a...
  • 18 篇 institute of ima...
  • 14 篇 university of ch...
  • 13 篇 shenyang institu...
  • 10 篇 school of comput...
  • 10 篇 school of scienc...
  • 10 篇 shanghai key lab...
  • 10 篇 peng cheng labor...
  • 10 篇 institutes for r...
  • 10 篇 shanghai key lab...
  • 9 篇 nanjing general ...
  • 9 篇 key lab of indus...
  • 9 篇 zhejiang lab
  • 8 篇 education minist...
  • 8 篇 key laboratory o...
  • 8 篇 shanghai key lab...
  • 7 篇 key laboratory o...
  • 7 篇 image processing...
  • 7 篇 key laboratory o...

作者

  • 47 篇 zhai guangtao
  • 30 篇 guangtao zhai
  • 30 篇 min xiongkuo
  • 26 篇 xiaokang yang
  • 22 篇 zhu xiuchang
  • 21 篇 jun wang
  • 21 篇 yang xiaokang
  • 20 篇 song li
  • 19 篇 yang hua
  • 19 篇 fan zhun
  • 17 篇 feng liu
  • 16 篇 sun wei
  • 16 篇 xiuchang zhu
  • 15 篇 zhang wenjun
  • 15 篇 gan zongliang
  • 15 篇 xie rong
  • 14 篇 hua yang
  • 13 篇 dong hu
  • 13 篇 hu dong
  • 12 篇 wenjun zhang

语言

  • 850 篇 英文
  • 21 篇 中文
  • 14 篇 其他
检索条件"机构=Key Lab of Image Processing and Image Communication"
885 条 记 录,以下是371-380 订阅
排序:
AIM 2019 challenge on real-world image super-resolution: Methods and results
arXiv
收藏 引用
arXiv 2019年
作者: Lugmayr, Andreas Danelljan, Martin Timofte, Radu Fritsche, Manuel Gu, Shuhang Purohit, Kuldeep Kandula, Praveen Suin, Maitreya Rajagopalan, A.N. Joon, Nam Hyung Won, Yu Seung Kim, Guisik Kwon, Dokyeong Hsu, Chih-Chung Lin, Chia-Hsiang Huang, Yuanfei Sun, Xiaopeng Lu, Wen Li, Jie Gao, Xinbo Bell-Kligler, Sefi Computer Vision Lab ETH Zurich Indian Institute Of Technology Madras India Image Communication & Signal Processing Laboratory Hanyang University Seoul Korea Republic of CVML Chung-Ang University Department Management Information Systems National Pingtung University of Science and Technology Department of Electrical Engineering National Cheng-Kung University Xidian University Weizmann Institute of Science Israel
This paper reviews the AIM 2019 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting, where paired true high and low-resol... 详细信息
来源: 评论
A Fast Quality Scalable Video Coding Method Based on Compressed Sensing
A Fast Quality Scalable Video Coding Method Based on Compres...
收藏 引用
2018 3rd International Conference on Electrical, Automation and Mechanical Engineering(EAME 2018)
作者: Min Sun Dong Hu Jianyu Ding Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications
This paper presents a fast quality scalable video coding method based on compressed sensing(CS). The proposed method obtained the coding scheme of the enhancement MJU by using the interlayer and spatial correlation an... 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
3D-EPI Blip-Up/Down Acquisition (BUDA) with CAIPI and Joint Hankel Structured Low-Rank Reconstruction for Rapid Distortion-Free High-Resolution T2* Mapping
arXiv
收藏 引用
arXiv 2022年
作者: Chen, Zhifeng Liao, Congyu Cao, Xiaozhi Poser, Benedikt A. Xu, Zhongbiao Lo, Wei-Ching Wen, Manyi Cho, Jaejin Tian, Qiyuan Wang, Yaohui Feng, Yanqiu Xia, Ling Chen, Wufan Liu, Feng Bilgic, Berkin School of Biomedical Engineering Guangdong Provincial Key Laboratory of Medical Image Processing Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology Southern Medical University Guangzhou China Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital CharlestownMA United States Department of Radiology Harvard Medical School CharlestownMA United States Department of Data Science and AI Faculty of IT Monash University ClaytonVIC Australia Department of Radiology Stanford University Stanford CA United States Maastricht Brain Imaging Center Faculty of Psychology and Neuroscience University of Maastricht Netherlands Department of Radiotherapy Cancer Center Guangdong Provincial People's Hospital Guangdong Academy of Medical Science Guangzhou China Siemens Medical Solutions BostonMA United States Department of Chemical Pathology The Chinese University of Hong Kong Hong Kong Division of Superconducting Magnet Science and Technology Institute of Electrical Engineering Chinese Academy of Sciences Beijing China Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence Key Laboratory of Mental Health of the Ministry of Education Southern Medical University Guangzhou China Department of Biomedical Engineering Zhejiang University Hangzhou China Research Center for Healthcare Data Science Zhejiang Lab Hangzhou China School of Information Technology and Electrical Engineering The University of Queensland BrisbaneQLD Australia Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology CambridgeMA United States
Purpose: This work aims to develop a novel distortion-free 3D-EPI acquisition and image reconstruction technique for fast and robust, high-resolution, whole-brain imaging as well as quantitative T2* mapping. Methods: ... 详细信息
来源: 评论
A Combined Texture-Shape Global 3D Feature Descriptor for Object Recognition and Grasping  3
A Combined Texture-Shape Global 3D Feature Descriptor for Ob...
收藏 引用
3rd International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration, ICIICII 2017
作者: Fan, Zhun Li, Zhongxing Li, Wenji You, Yugen Chen, Wenzhao Li, Chong Key Lab of Digital Signal and Image Processing of Guangdong Province Shantou University Guangdong Shantou515063 China
This paper presents a global 3D feature descriptor for object recognition and grasping. The proposed descriptor stems from the clustered viewpoint feature histogram (CVFH) feature descriptor. Since the CVFH feature de... 详细信息
来源: 评论
QUBIQ: Uncertainty Quantification for Biomedical image Segmentation Challenge
arXiv
收藏 引用
arXiv 2024年
作者: Li, Hongwei Bran Navarro, Fernando Ezhov, Ivan Bayat, Amirhossein Das, Dhritiman Kofler, Florian Shit, Suprosanna Waldmannstetter, Diana Paetzold, Johannes C. Hu, Xiaobin Wiestler, Benedikt Zimmer, Lucas Amiranashvili, Tamaz Prabhakar, Chinmay Berger, Christoph Weidner, Jonas Alonso-Basanta, Michelle Rashid, Arif Baid, Ujjwal Adel, Wesam Alis, Deniz Baheti, Bhakti Bai, Yingbin Bhat, Ishaan Cetindag, Sabri Can Chen, Wenting Cheng, Li Dutande, Prasad Dular, Lara Elattar, Mustafa A. Feng, Ming Gao, Shengbo Huisman, Henkjan Hu, Weifeng Innani, Shubham Ji, Wei Karimi, Davood Kuijf, Hugo J. Kwak, Jin Tae Le, Hoang Long Li, Xiang Lin, Huiyan Liu, Tongliang Ma, Jun Ma, Kai Ma, Ting Oksuz, Ilkay Holland, Robbie Oliveira, Arlindo L. Pal, Jimut Bahan Pei, Xuan Qiao, Maoying Saha, Anindo Selvan, Raghavendra Shen, Linlin Silva, Joao Lourenco Spiclin, Ziga Talbar, Sanjay Wang, Dadong Wang, Wei Wang, Xiong Wang, Yin Xi, Ruiling Xu, Kele Yang, Yanwu Yergin, Mert Yu, Shuang Zeng, Lingxi Zhang, YingLin Zhao, Jiachen Zheng, Yefeng Zukovec, Martin Do, Richard Becker, Anton Simpson, Amber Konukoglu, Ender Jakab, Andras Bakas, Spyridon Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Harvard Medical School United States Department of Quantitative Biomedicine University of Zurich Switzerland University Children’s Hospital Zurich University of Zurich Switzerland Department of Radioncology and Radiation Theraphy Klinikum rechts der Isar Technical University of Munich Germany Department of Information Technology and Electrical Engineering ETH-Zurich Switzerland Department of Radiology Memorial Sloan Kettering Cancer Center New York City United States Department of Biomedical and Molecular Sciences Queen’s University Canada TranslaTUM - Central Institute for Translational Cancer Research Technical University of Munich Germany McGovern Institute Massachusetts Institute of Technology United States Institute for Diagnostic and Interventional Radiology Unveristy Zurich Hospital Switzerland BioMedIA Imperial College London United Kingdom Department of Radiation Oncology University of Pennsylvania PA United States University of Pennsylvania PA United States Department of Radiation Oncology Winship Cancer Institute of Emory University Georgia United States Nile University Cairo Egypt Department of Medical Sciences Acibadem University Istanbul Turkey Shri Guru Gobind Singhji Institute of Engineering and Technology Maharashtra Nanded India Trustworthy Machine Learning Lab University of Sydney Australia Image Sciences Institute University Medical Center Utrecht Netherlands Computer Engineering Department Istanbul Technical University Istanbul Turkey School of Computer Science Shenzhen University Shenzhen China University of Alberta United States University of Ljubljana Faculty of Electrical Engineering Ljubljana Slovenia Tongji University Shanghai China OPPO Research Institute Shanghai China School of Biological and Medical Engineering Beihang University Beijing China Harvard Medical School Boston
Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a significant challenge in achieving consis... 详细信息
来源: 评论
A directional-progressive search method for infrared small target detection  3
A directional-progressive search method for infrared small t...
收藏 引用
3rd Optoelectronics Global Conference, OGC 2018
作者: Zhang, Xiangyue Ding, Qinghai Luo, Haibo Hui, Bin Chang, Zheng Zhang, Junchao Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Opto-Electronic Information Processing CAS Shenyang110016 China Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang110016 China Space Star Technology Co. Ltd Beijing100086 China
Infrared small target detection plays a key role in infrared precision guidance and infrared early-warning system. It has been a difficult problem for researchers to study on how to detect targets accurately at a long... 详细信息
来源: 评论
Object tracking in hyperspectral videos with convolutional features and kernelized correlation filter
arXiv
收藏 引用
arXiv 2018年
作者: Qian, Kun Zhou, Jun Xiong, Fengchao Zhou, Huixin Du, Juan Lab of Optoelectronic Imaging and Image Processing Xidian University Xi’an China School of Information and Communication Technology Griffith University Brisbane Australia College of Computer Science Zhejiang University Hangzhou China
Target tracking in hyperspectral videos is a new research topic. In this paper, a novel method based on convolutional network and Kernelized Correlation Filter (KCF) framework is presented for tracking objects of inte... 详细信息
来源: 评论
Automatic exudate detection in color fundus images  13th
Automatic exudate detection in color fundus images
收藏 引用
13th International Forum of Digital TV and Wireless Multimedia communication, IFTC 2016
作者: Qi, Fucong Li, Guo Zheng, Shibao Institute of Image Communication and Network Engineering Shanghai Key Labs of Digital Media Processing and Transmission Shanghai Jiao Tong University Shanghai200240 China
Diabetic retinopathy is a major cause of blindness in working age population and exudates are considered the most significant characteristics of diabetic retinopathy. Therefore, automatic exudate detection is benefici... 详细信息
来源: 评论
An effective crowd property analysis system for video surveillance application  13th
An effective crowd property analysis system for video survei...
收藏 引用
13th International Forum of Digital TV and Wireless Multimedia communication, IFTC 2016
作者: Yang, Shuying Yang, Hua Li, Jijia Zhu, Ji Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai China
For public security, an intelligent video surveillance system that can analyze large-scale crowd scenes has become an urgent need. In this paper, we propose a system that integrates multiple crowd properties, includin... 详细信息
来源: 评论