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检索条件"机构=Shenzhen Key Laboratory of Advance Machine Learning and Applications"
87 条 记 录,以下是81-90 订阅
排序:
A model-guided deep network for limited-angle computed tomography
arXiv
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arXiv 2020年
作者: Wang, Wei Xia, Xiang-Gen He, Chuanjiang Ren, Zemin Lu, Jian Wang, Tianfu Lei, Baiying School of Biomedical Engineering Shenzhen University National-Regional Key Technology Engineering Laboratory for Medical Ultrasound Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen China Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States College of Mathematics and Statistics Chongqing University Chongqing China College of Mathematics and Physics Chongqing University of Science and Technology Chongqing China Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen China
In this paper, we first propose a variational model for the limited-angle computed tomography (CT) image reconstruction and then convert the model into an end-to-end deep network. We use the penalty method to solve th... 详细信息
来源: 评论
Bayesian network based label correlation analysis for multi-label classifier chain
arXiv
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arXiv 2019年
作者: Wang, Ran Ye, Suhe Li, Ke Kwong, Sam College of Mathematics and Statistics Shenzhen University Shenzhen518060 China Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China Department of Computer Science University of Exeter ExeterEX4 4QF United Kingdom Department of Computer Science City University of Hong Kong 83 Tat Chee Avenue Kowloon Hong Kong
Classifier chain (CC) is a multi-label learning approach that constructs a sequence of binary classifiers according to a label order. Each classifier in the sequence is responsible for predicting the relevance of one ... 详细信息
来源: 评论
Analysis of a Direct Separation Method Based on Adaptive Chirplet Transform for Signals with Crossover Instantaneous Frequencies
arXiv
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arXiv 2022年
作者: Chui, Charles K. Jiang, Qingtang Li, Lin Lu, Jian Menlo Park residence CA94025 United States Department of Mathematics & Statistics University of Missouri-St. Louis St. LouisMO63121 United States School of Electronic Engineering Xidian University Xi'An710071 China Shenzhen Key Laboratory of Advanced Machine Learning and Applications College of Mathematics & Statistics Shenzhen University Shenzhen518060 China
In many applications, it is necessary to retrieve the sub-signal building blocks of a multicomponent signal, which is usually non-stationary in real-world and real-life applications. Empirical mode decomposition (EMD)... 详细信息
来源: 评论
A signal separation method based on adaptive continuous wavelet transform and its analysis
arXiv
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arXiv 2020年
作者: Chui, Charles K. Jiang, Qingtang Li, Lin Lu, Jian College of Mathematics & Statistics Shenzhen University Shenzhen518060 China Department of Mathematics Hong Kong Baptist University Hong Kong Department of Mathematics & Statistics University of Missouri-St. Louis St. LouisMO63121 United States School of Electronic Engineering Xidian University Xi'an710071 China Shenzhen Key Laboratory of Advanced Machine Learning and Applications College of Mathematics & Statistics Shenzhen University Shenzhen518060 China
In nature and engineering world, the measured signals are usually affected by multiple complicated factors and they appear as multicomponent non-stationary modes. In many situations we need to separate these signals t... 详细信息
来源: 评论
Analysis of an Adaptive Short-Time Fourier Transform-Based Multicomponent Signal Separation Method Derived from Linear Chirp Local Approximation
arXiv
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arXiv 2020年
作者: Chui, Charles K. Jiang, Qingtang Li, Lin Lu, Jian College of Mathematics & Statistics Shenzhen University Shenzhen518060 China Department of Mathematics Hong Kong Baptist University Hong Kong Department of Math & Computer Sci. Univ. of Missouri-St. Louis St. LouisMO63121 United States School of Electronic Engineering Xidian University Xian710071 China Shenzhen Key Laboratory of Advanced Machine Learning and Applications College of Mathematics & Statistics Shenzhen University Shenzhen518060 China
The synchrosqueezing transform (SST) has been developed as a powerful EMD-like tool for instantaneous frequency (IF) estimation and component separation of non-stationary multicomponent signals. Recently, a direct met... 详细信息
来源: 评论
Multi-label Classification with High-rank and High-order Label Correlations
arXiv
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arXiv 2022年
作者: Si, Chongjie Jia, Yuheng Wang, Ran Zhang, Min-Ling Feng, Yanghe Qu, Chongxiao The Chien-Shiung Wu College Southeast University Nanjing210096 China The MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai200240 China The School of Computer Science and Engineering Southeast University Nanjing210096 China Ministry of Education China School of Computing & Information Sciences Caritas Institute of Higher Education Hong Kong The Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China The School of Mathematical Science Shenzhen University Shenzhen518060 China Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China The College of Systems Engineering National University of Defense Technology China The 52nd Research Institute of China Electronics Technology Group China
Exploiting label correlations is important to multi-label classification. Previous methods capture the high-order label correlations mainly by transforming the label matrix to a latent label space with low-rank matrix... 详细信息
来源: 评论
-minimization methods for image restoration problems based on wavelet frames
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Inverse Problems 2019年 第6期35卷 064001-064001页
作者: Jian Lu Ke Qiao Xiaorui Li Zhaosong Lu Yuru Zou Shenzhen Key Laboratory of Advanced Machine Learning and Applications College of Mathematics and Statistics Shenzhen University Shenzhen People’s Republic of China College of Mathematics and Statistics Shenzhen University Shenzhen People’s Republic of China Department of Mathematics Simon Fraser University Burnaby Canada
In this paper we consider a class of -minimization and wavelet frame-based models for image deblurring and denoising. Mathematically, they can be formulated as minimizing the sum of a data fidelity term and the l0-...
来源: 评论