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检索条件"机构=Pattern Recognition and Image Processing"
1790 条 记 录,以下是1731-1740 订阅
排序:
A new method for removing random-valued impulse noise
Lecture Notes in Computer Science (including subseries Lectu...
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8836卷 9-16页
作者: Jin, Qiyu Bai, Li Yang, Jie Grama, Ion Liu, Quansheng Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University No. 800 Dongchuan Road Minhang District Shanghai200240 China School of Computer Science University of Nottingham United Kingdom Laboratoire de Mathmatiques de Bretagne Atlantique Université de Bretagne-Sud UMR 6205 Campus de Tohaninic BP 573 Vannes56017 France
A new algorithm for removing random-valued impulse noise is *** use a standardized version of the Rank Ordered Absolute Differences statistic of Garnett et al. [1] to attribute weights to noisy pixels. These weights a... 详细信息
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Novel way achieving 3D reconstruction of actual human face using multi images
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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2008年 第4期36卷 661-666页
作者: Hou, Wen-Guang Chan, Tai-Wai Ding, Ming-Yue Image Processing and Intelligent Control Key Laboratory Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Industrial Centre Hong Kong Polytechnic University Hong Kong Hong Kong
A novel way achieving geometrical reconstruction of actual human face through projecting two types of texture on face in short time is advanced. The first type texture is stripe which is used to establish parallax gri... 详细信息
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Generalization Properties of hyper-RKHS and its Applications
arXiv
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arXiv 2018年
作者: Liu, Fanghui Shi, Lei Huang, Xiaolin Yang, Jie Suykens, Johan A.K. Department of Electrical Engineering ESAT-STADIUS KU Leuven Kasteelpark Arenberg 10 LeuvenB-3001 Belgium Shanghai Key Laboratory for Contemporary Applied Mathematics School of Mathematical Sciences Fudan University Shanghai200433 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China
This paper generalizes regularized regression problems in a hyper-reproducing kernel Hilbert space (hyper-RKHS), illustrates its utility for kernel learning and out-of-sample extensions, and proves asymptotic converge... 详细信息
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Boosting discriminative model for moving cast shadow detection
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Jisuanji Xuebao/Chinese Journal of Computers 2007年 第8期30卷 1295-1301页
作者: Zha, Yu-Fei Chu, Ying Wang, Xun Ma, Shi-Ping Bi, Du-Yan Signal and Information Processing Laboratory Engineering College Air Force Engineering University Xi'an 710038 China Key Laboratory for Image Processing and Intelligent Control Institute of Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. and Technol. Wuhan 430074 China
Moving cast shadow causes serious problem while segmenting and extracting foreground from image sequences, due to the misclassification of moving shadow as foreground. This paper proposes a Boosting discriminative mod... 详细信息
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Predicting functional impact of single amino acid polymorphisms by integrating sequence and structural features
Predicting functional impact of single amino acid polymorphi...
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IEEE International Conference on Systems Biology
作者: Mingjun Wang Hong-Bin Shen Tatsuya Akutsu Jiangning Song State Engineering Laboratory for Industrial Enzymes Tianjin Institute of Industrial Biotechnology Chinese Academy of Sciences (CAS) Tianjin China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Bioinformatics Center Institute for Chemical Research Kyoto University Uji Kyoto Japan Department of Biochemistry and Molecular Biology Faculty of Medicine Monash University Melbourne VIC Australia
Single amino acid polymorphisms (SAPs) are the most abundant form of known genetic variations associated with human diseases. It is of great interest to study the sequence-structure-function relationship underlying SA... 详细信息
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Robust occupancy detection from stereo images
Robust occupancy detection from stereo images
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International Conference on Intelligent Transportation
作者: B. Alefs M. Clabian H. Bischof W. Kropatsch F. Khairallah Advanced Computer Vision GmbH-ACV Vienna Austria Advanced Computer Vision GmbH-ACV Austria Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Computer Science Department University of Technology Vienna Vienna Austria TRW Automotive GmbH Farmington Hills MI USA
Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occup... 详细信息
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Efficient spatialtemporal context modeling for action recognition?
arXiv
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arXiv 2021年
作者: Cao, Congqi Lu, Yue Zhang, Yifan Jiang, Dongmei Zhang, Yanning Natl. Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Shaanxi Provincial Key Lab on Speech and Image Information Processing School of Computer Science Northwestern Poly-technical University Xi'an710129 China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing100190 China
Contextual information plays an important role in action recognition. Local operations have difficulty to model the relation between two elements with a long-distance interval. However, directly modeling the contextua... 详细信息
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Learning data-adaptive non-parametric kernels
The Journal of Machine Learning Research
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The Journal of Machine Learning Research 2020年 第1期21卷 8590-8628页
作者: Fanghui Liu Xiaolin Huang Chen Gong Jie Yang Li Li Department of Electrical Engineering ESAT-STADIUS KU Leuven Belgium Institute of Image Processing and Pattern Recognition Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China PCA Lab Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology China and Department of Computing Hong Kong Polytechnic University Hong Kong SAR China Department of Automation BNRist Tsinghua University China
In this paper, we propose a data-adaptive non-parametric kernel learning framework in margin based kernel methods. In model formulation, given an initial kernel matrix, a data-adaptive matrix with two constraints is i... 详细信息
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COVID-MTL: Multitask learning with shift3D and random-weighted loss for automated diagnosis and severity assessment of COVID-19
arXiv
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arXiv 2020年
作者: Bao, Guoqing Chen, Huai Liu, Tongliang Gong, Guanzhong Yin, Yong Wang, Lisheng Wang, Xiuying School of Computer Science The University of Sydney J12/1 Cleveland St Darlington SydneyNSW2008 Australia Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Department of Radiation Oncology Shandong Cancer Hospital and Institute Shandong First Medical University Shandong Academy of Medical Sciences Jinan250117 China
There is an urgent need for automated methods to assist accurate and effective assessment of COVID-19. Radiology and nucleic acid test (NAT) are complementary COVID-19 diagnosis methods. In this paper, we present an e... 详细信息
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Sparse generalized canonical correlation analysis: Distributed alternating iteration based approach
arXiv
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arXiv 2020年
作者: Cai, Jia Lv, Kexin Huo, Junyi Huang, Xiaolin Yang, Jie School of Statistics and Mathematics Guangdong University of Finance & Economics Big Data and Educational Statistics Application Laboratory 21 Chisha Road Guangzhou Guangdong510320 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University MOE Key Laboratory of System Control and Information Processing 800 Dongchuan Road Shanghai200240 China School of Electronics and Computer Science University of Southampton University Road SouthamptonSO17 1BJ United Kingdom
Sparse canonical correlation analysis (CCA) is a useful statistical tool to detect latent information with sparse structures. However, sparse CCA works only for two datasets, i.e., there are only two views or two dist... 详细信息
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