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检索条件"机构=Institute for Pattern Recognition and Image Processing Computer Science Department"
298 条 记 录,以下是241-250 订阅
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Matching confidence analysis method based on tests of hypotheses
Matching confidence analysis method based on tests of hypoth...
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IEEE International Conference on Systems, Man and Cybernetics
作者: Nong Sang Ruolin Wang Tianxu Zhang Institute for Pattern Recognition and Artificial Intelligence State E ducation Commission Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei China Department of Civil Engineering Wuhan University of Hydraulic and Electrical Engineering Hubei China
Matching confidence is an important element for evaluating image matching quality. A method is presented which uses the technique of tests of hypotheses to determine image matching confidence under a certain testing l... 详细信息
来源: 评论
Modeling Inter-Intra Heterogeneity for Graph Federated Learning
arXiv
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arXiv 2024年
作者: Yu, Wentao Chen, Shuo Tong, Yongxin Gu, Tianlong Gong, Chen School of Computer Science and Engineering Nanjing University of Science and Technology China Center for Advanced Intelligence Project RIKEN Japan State Key Laboratory of Complex & Critical Software Environment Beihang University China Jinan University China Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China
Heterogeneity is a fundamental and challenging issue in federated learning, especially for the graph data due to the complex relationships among the graph nodes. To deal with the heterogeneity, lots of existing method... 详细信息
来源: 评论
Mixed one-bit compressive sensing with application to overexposure correction for CT reconstruction
arXiv
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arXiv 2017年
作者: Huang, Xiaolin Xia, Yan Shi, Lei Huang, Yixing Yan, Ming Hornegger, Joachim Maier, Andreas Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Department of Radiology Stanford University CA United States School of Mathematical Sciences Fudan University Shanghai China Pattern Recognition Lab of Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Department of Computational Mathematics Science and Engineering Michigan State University MI United States
When a measurement falls outside the quantization or measurable range, it becomes saturated and cannot be used in classical reconstruction methods. For example, in C-arm angiography systems, which provide projection r... 详细信息
来源: 评论
Hybrid Data-Free Knowledge Distillation
arXiv
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arXiv 2024年
作者: Tang, Jialiang Chen, Shuo Gong, Chen School of Computer Science and Engineering Nanjing University of Science and Technology China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education China Jiangsu Key Laboratory of Image and Video Understanding for Social Security China Center for Advanced Intelligence Project RIKEN Japan Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China
Data-free knowledge distillation aims to learn a compact student network from a pre-trained large teacher network without using the original training data of the teacher network. Existing collection-based and generati... 详细信息
来源: 评论
Evaluating deformation patterns of the thoracic aorta in gated CTA sequences
Evaluating deformation patterns of the thoracic aorta in gat...
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IEEE International Symposium on Biomedical Imaging
作者: Ernst Schwartz Roman Gottardi Johannes Holfeld Christian Loewe Martin Czerny Georg Langs Computational Image Analysis and Radiology Lab (CIR) Medical University of Vienna Austria Pattern Recognition and Image Processing Group University of Technology Vienna Austria Division of Cardiothoracic Surgery Department of Surgery Medical University of Vienna Austria Division of Interventional Radiology Department of Radiology Medical University of Vienna Austria Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology USA
Cardiovascular interventions in the region of the aortic isthmus such as stent-grafting and vessel transposition introduce substantial changes in the deformation properties of the affected vessels. The changes play a ... 详细信息
来源: 评论
Dim small targets fusion detection in infrared image
Dim small targets fusion detection in infrared image
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International Conference on Machine Learning and Cybernetics (ICMLC)
作者: Yu-Qiu Sun Yu Zheng Jin-Wen Tian Jian Liu School of Information and Mathematics Yangtze University Jingzhou China State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China State Education Commission Key Laboratory for Image Processing and Intelligent Control Department of Electronic Information and Enginery of Huazhong University of Science and Technology Wuhan China
To infrared images, the contrast of target and background is low, dim small targets have no concrete shapes and their textures cannot be reliable predicted. The paper puts forward a novel algorithm to fuse mid-wave an... 详细信息
来源: 评论
Background suppression based-on wavelet transformation to detect infrared target
Background suppression based-on wavelet transformation to de...
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International Conference on Machine Learning and Cybernetics (ICMLC)
作者: Yu-Qiu Sun Jin-Wen Tian Jian Liu State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China School of Information and Mathematics Yangtze University Jinzhou China State Education Commission Key Laboratory for Image Processing and Intelligent Control Department of Electronic Information and Enginery Huazhong University of Science and Technology Wuhan China
Target detection and location in infrared clutter background is very important to infrared search and track system. Especially for small target detection in infrared image in background of sea and sky, there are no ge... 详细信息
来源: 评论
A regularization approach for instance-based superset label learning
arXiv
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arXiv 2019年
作者: Gong, Chen Liu, Tongliang Tang, Yuanyan Yang, Jian Yang, Jie Tao, Dacheng School of Computer Science and Engineering Nanjing University of Science and Technology Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University School of Software Faculty of Engineering and Information Technology University of Technology Sydney UltimoNSW2007 Australia Faculty of Science and Technology University of Macau Macau999078 China College of Computer Science Chongqing University Chongqing400000 China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai200240 China School of Information Technologies Faculty of Engineering and Information Technologies University of Sydney J12/318 Cleveland St DarlingtonNSW2008 Australia
Different from the traditional supervised learning in which each training example has only one explicit label, Superset Label Learning (SLL) refers to the problem that a training example can be associated with a set o... 详细信息
来源: 评论
Partial Differential Equations is All You Need for Generating Neural Architectures - A Theory for Physical Artificial Intelligence Systems
arXiv
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arXiv 2021年
作者: Guo, Ping Huang, Kaizhu Xu, Zenglin Image Processing & Pattern Recognition Lab. Beijing Normal University Beijing100875 China Data Science Research Center Duke Kunshan University Jiangsu Kunshan215316 China School of Computer Science and Technology Harbin Institute of Technology at ShenZhen Peng Cheng National Lab Guangdong Shenzhen510855 China
In this work, we generalize the reaction-diffusion equation in statistical physics, Schrödinger equation in quantum mechanics, and Helmholtz equation in paraxial optics into the neural partial differential equati... 详细信息
来源: 评论
Fast signal recovery from saturated measurements by linear loss and nonconvex penalties
arXiv
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arXiv 2018年
作者: He, Fan Huang, Xiaolin Liu, Yipeng Yan, Ming Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University The MOE Key Laboratory of System Control and Information Processing Shanghai200240 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China The Department of Computational Mathematics Science and Engineering Michigan State University MI United States
Sign information is the key to overcoming the inevitable saturation error in compressive sensing systems, which causes information loss and results in bias. For sparse signal recovery from saturation, we propose to us... 详细信息
来源: 评论