咨询与建议

限定检索结果

文献类型

  • 42 篇 会议
  • 29 篇 期刊文献
  • 2 册 图书

馆藏范围

  • 73 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 41 篇 工学
    • 29 篇 计算机科学与技术...
    • 27 篇 软件工程
    • 11 篇 光学工程
    • 10 篇 信息与通信工程
    • 9 篇 机械工程
    • 7 篇 生物医学工程(可授...
    • 6 篇 生物工程
    • 5 篇 电气工程
    • 5 篇 控制科学与工程
    • 4 篇 仪器科学与技术
    • 3 篇 电子科学与技术(可...
    • 2 篇 化学工程与技术
    • 1 篇 力学(可授工学、理...
    • 1 篇 建筑学
    • 1 篇 航空宇航科学与技...
    • 1 篇 城乡规划学
  • 24 篇 理学
    • 10 篇 物理学
    • 8 篇 生物学
    • 7 篇 数学
    • 3 篇 化学
    • 2 篇 统计学(可授理学、...
    • 1 篇 地理学
  • 10 篇 管理学
    • 7 篇 管理科学与工程(可...
    • 5 篇 图书情报与档案管...
    • 3 篇 工商管理
  • 5 篇 医学
    • 5 篇 临床医学
    • 4 篇 基础医学(可授医学...
    • 4 篇 药学(可授医学、理...
  • 2 篇 经济学
    • 2 篇 应用经济学
  • 2 篇 法学
    • 2 篇 社会学
  • 1 篇 艺术学

主题

  • 10 篇 pattern recognit...
  • 8 篇 image segmentati...
  • 7 篇 feature extracti...
  • 6 篇 optical characte...
  • 6 篇 databases
  • 6 篇 training
  • 6 篇 character recogn...
  • 5 篇 support vector m...
  • 5 篇 face recognition
  • 5 篇 computer vision
  • 4 篇 computational mo...
  • 4 篇 face
  • 4 篇 text recognition
  • 3 篇 motion estimatio...
  • 3 篇 convolution
  • 3 篇 reservoirs
  • 3 篇 benchmark testin...
  • 3 篇 water resources
  • 3 篇 image color anal...
  • 3 篇 image recognitio...

机构

  • 8 篇 computer vision ...
  • 5 篇 national laborat...
  • 4 篇 center of comput...
  • 3 篇 institute of med...
  • 3 篇 l3i laboratory u...
  • 3 篇 university of ch...
  • 3 篇 cvpr unit indian...
  • 3 篇 computer vision ...
  • 2 篇 karachi pakistan
  • 2 篇 the center for v...
  • 2 篇 institute of dee...
  • 2 篇 paul c. lauterbu...
  • 2 篇 shanghai ai lab
  • 2 篇 computer vision ...
  • 2 篇 siat branch shen...
  • 2 篇 dept. of profess...
  • 2 篇 computer vision ...
  • 2 篇 computer vision ...
  • 2 篇 jiangsu provinci...
  • 2 篇 centre for patte...

作者

  • 9 篇 umapada pal
  • 9 篇 pal umapada
  • 5 篇 imran siddiqi
  • 5 篇 lladós josep
  • 4 篇 escalera sergio
  • 4 篇 karatzas dimosth...
  • 4 篇 li stan z.
  • 4 篇 stan z. li
  • 4 篇 wan jun
  • 4 篇 josep lladós
  • 3 篇 guo guodong
  • 3 篇 maier andreas
  • 3 篇 bunke horst
  • 3 篇 partha pratim ro...
  • 3 篇 chawki djeddi
  • 3 篇 momina moetesum
  • 3 篇 escalante hugo j...
  • 3 篇 dey sounak
  • 3 篇 qiao yu
  • 3 篇 dutta anjan

语言

  • 71 篇 英文
  • 1 篇 其他
  • 1 篇 中文
检索条件"机构=Center of Computer Vision and Pattern Recognition"
73 条 记 录,以下是51-60 订阅
排序:
An End-to-End Video Text Detector with Online Tracking
An End-to-End Video Text Detector with Online Tracking
收藏 引用
International Conference on Document Analysis and recognition
作者: Hongyuan Yu Chengquan Zhang Xuan Li Junyu Han Errui Ding Liang Wang University of Chinese Academy of Sciences (UCAS) Center for Research on Intelligent Perception and Computing (CRIPAC) National Laboratory of Pattern Recognition (NLPR) Department of Computer Vision Technology(VIS) Baidu Inc. Chinese Academy of Sciences Artificial Intelligence Research (CAS-AIR)
Video text detection is considered as one of the most difficult tasks in document analysis due to the following two challenges: 1) the difficulties caused by video scenes, i.e., motion blur, illumination changes, and ... 详细信息
来源: 评论
Exploring Fusion Strategies for Accurate RGBT Visual Object Tracking
arXiv
收藏 引用
arXiv 2022年
作者: Tang, Zhangyong Xu, Tianyang Li, Hui Wu, Xiao-Jun Zhu, XueFeng Kittler, Josef Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence School of Artificial Intelligence and Computer Science Jiangnan University Wuxi214122 China The Center for Vision Speech and Signal Processing University of Surrey GuildfordGU2 7XH United Kingdom
We address the problem of multi-modal object tracking in video and explore various options of fusing the complementary information conveyed by the visible (RGB) and thermal infrared (TIR) modalities including pixel-le... 详细信息
来源: 评论
RFN-Nest: An end-to-end residual fusion network for infrared and visible images
arXiv
收藏 引用
arXiv 2021年
作者: Li, Hui Wu, Xiao-Jun Kittler, Josef Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence School of Artificial Intelligence and Computer Science Jiangnan University Wuxi214122 China The Center for Vision Speech and Signal Processing University of Surrey GuildfordGU2 7XH United Kingdom
In the image fusion field, the design of deep learning-based fusion methods is far from routine. It is invariably fusion-task specific and requires a careful consideration. The most difficult part of the design is to ... 详细信息
来源: 评论
Evaluation of feature sensitivity to training data inaccuracy in detection of retinal lesions
Evaluation of feature sensitivity to training data inaccurac...
收藏 引用
Workshops on Image Processing Theory, Tools and Applications, IPTA
作者: Lauri Laaksonen Antti Hannuksela Ela Claridge Pauli Fält Markku Hauta-Kasari Hannu Uusitalo Lasse Lensu Machine Vision and Pattern Recognition Laboratory Lappeenranta university of Technology Lappeenranta Finland School of Computer Science The University of Birmingham United Kingdom School of Computing University of Eastern Finland Finland Department of Ophthalmology University of Tampere Finland TAUH Eye Center Tampere University Hospital Finland
computer aided diagnostic and segmentation tools have become increasingly important in reducing the workload of medical experts performing diagnosis, monitoring and documentation of various eye diseases such as age-re... 详细信息
来源: 评论
Feature refinement: An expression-specific feature learning and fusion method for micro-expression recognition
arXiv
收藏 引用
arXiv 2021年
作者: Zhou, Ling Mao, Qirong Huang, Xiaohua Zhang, Feifei Zhang, Zhihong School of Computer Science and Communication Engineering Jiangsu University ZhenjiangJiangsu212013 China School of Computer Engineering Nanjing Institute of Technology China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China Xiamen University Xiamen China Center for Machine Vision and Signal Analysis University of Oulu Finland
Micro-Expression recognition has become challenging, as it is extremely difficult to extract the subtle facial changes of micro-expressions. Recently, several approaches proposed several expression-shared features alg... 详细信息
来源: 评论
When Face recognition Meets with Deep Learning: An Evaluation of Convolutional Neural Networks for Face recognition
When Face Recognition Meets with Deep Learning: An Evaluatio...
收藏 引用
International Conference on computer vision Workshops (ICCV Workshops)
作者: Guosheng Hu Yongxin Yang Dong Yi Josef Kittler William Christmas Stan Z. Li Timothy Hospedales Centre for Vision Speech and Signal Processing University of Surrey UK Indicates equal contribution LEAR team Inria Grenoble Rhone-Alpes Montbonnot France Electronic Engineering and Computer Science Queen Mary University of London UK Chinese Academy of Sciences Center for Biometrics and Security Research & National Laboratory of Pattern Recognition China
Deep learning, in particular Convolutional Neural Network (CNN), has achieved promising results in face recognition recently. However, it remains an open question: why CNNs work well and how to design a 'good'... 详细信息
来源: 评论
ICDAR2019 Robust reading challenge on multi-lingual scene text detection and recognition – RRC-MLT-2019
arXiv
收藏 引用
arXiv 2019年
作者: Nayef, Nibal Patel, Yash Busta, Michal Chowdhury, Pinaki Nath Karatzas, Dimosthenis Khlif, Wafa Matas, Jiri Pal, Umapada Burie, Jean-Christophe Liu, Cheng-lin Ogier, Jean-Marc L3i Laboratory University of La Rochelle France Computer Vision Center Universitat Autònoma de Barcelona Spain CVPR unit Indian Statistical Institute India Robotics Institute Carnegie Mellon Universiry Pittsburgh United States Center for Machine Perception Department of Cybernetics Czech Technical University Prague Czech Republic National Laboratory of Pattern Recognition Institute of Automation of Chinese Academy of Sciences China
With the growing cosmopolitan culture of modern cities, the need of robust Multi-Lingual scene Text (MLT) detection and recognition systems has never been more immense. With the goal to systematically benchmark and pu... 详细信息
来源: 评论
BasicVSR: The search for essential components in video super-resolution and beyond
arXiv
收藏 引用
arXiv 2020年
作者: Chan, Kelvin C.K. Wang, Xintao Yu, Ke Dong, Chao Loy, Chen Change S-Lab Nanyang Technological University Singapore Applied Research Center Tencent PCG CUHK – SenseTime Joint Lab Chinese University of Hong Kong Shenzhen Key Lab of Computer Vision and Pattern Recognition SIAT-SenseTime Joint Lab Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society China
Video super-resolution (VSR) approaches tend to have more components than the image counterparts as they need to exploit the additional temporal dimension. Complex designs are not uncommon. In this study, we wish to u... 详细信息
来源: 评论
Collaborative Multi-View Convolutions With Gating For Accurate And Fast Volumetric Medical Image Segmentation
Collaborative Multi-View Convolutions With Gating For Accura...
收藏 引用
IEEE International Symposium on Biomedical Imaging
作者: Cheng Li Jin Ye Junjun He Shanshan Wang Lixu Gu Yu Qiao Paul C. Lauterbur Research Center for Biomedical Imaging SIAT CAS Shenzhen China Shenzhen Key Lab of Computer Vision and Pattern Recognition SIAT-SenseTime Joint Lab SIAT CAS Shenzhen China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China School of Biomedical Engineering/the Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China
Due to their high capacity in capturing 3D spatial information, 3D Fully Convolutional Neural Networks (3D FCNs), especially 3D U-Net, are prevalent for volumetric medical image segmentation. However, 3D convolutions ... 详细信息
来源: 评论
A new convolutional neural network based on a saprse convolutional layer for animal face detection
TechRxiv
收藏 引用
TechRxiv 2021年
作者: Jarraya, Islem BenSaid, Fatma Ouarda, Wael Pal, Umapada Alimi, Adel M. BP 1173 Sfax3038 Tunisia Digital Research Center of Sfax B.P. 275 Sakiet Ezzit Sfax3021 Tunisia Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B.T. Road Kolkata700 108 India Department of Electrical and Electronic Engineering Science Faculty of Engineering and the Built Environment University of Johannesburg South Africa
This paper focuses on the face detection problem of three popular animal categories that need control such as horses, cats and dogs. To be precise, a new Convolutional Neural Network for Animal Face Detection (CNNAFD)... 详细信息
来源: 评论