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检索条件"机构=Image Processing and Pattern Recognition Laboratory Beijing Normal University"
149 条 记 录,以下是41-50 订阅
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An Effective Method for Modeling Two-dimensional Sky Background of LAMOST
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Proceedings of the International Astronomical Union 2017年 第S325期12卷 63-66页
作者: Hasitieer Haerken Fuqing Duan Jiannan Zhang Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University 100875 Beijing China email: fqduan@bnu.edu.cnpguo@*** National Astronomical Observatories & Chinese Academy of Sciences 100012 Beijing China email: hastear@***jnzhang@***
Each CCD of LAMOST accommodates 250 spectra, while about 40 are used to observe sky background during real observations. How to estimate the unknown sky background information hidden in the observed 210 celestial spec... 详细信息
来源: 评论
Study of point spread function of astronomical object imaging
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International Conference on Information Science and Applications, ICISA 2016
作者: Yu, Jian Yin, Qian Guo, Ping College of Computer and Information Engineering Hanshan Normal University ChaozhouGuangdong521041 China Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing100875 China
The research of point spread function (PSF) of astronomical object imaging is very important to the astronomical image restoration. In this paper, the simulated atmospheric turbulent phase screen, the short exposure P... 详细信息
来源: 评论
image Stitching with single-hidden layer feedforward Neural Networks
Image Stitching with single-hidden layer feedforward Neural ...
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International Joint Conference on Neural Networks
作者: Min Yan Qian Yin Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University
In this paper, a novel image stitching method is proposed, which utilizes scale-invariant feature transform (SIFT) feature and single-hidden layer feedforward neural network (SLFN) to get higher precision of parameter... 详细信息
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Kernel Selection with Evolutionary Algorithm for Multiple Kernel Independent Component Analysis
Kernel Selection with Evolutionary Algorithm for Multiple Ke...
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International Joint Conference on Neural Networks
作者: Peng Wu Qian Yin Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University
Kernel independent component analysis (KICA) has an important application in blind source separation, in which how to select the optimal kernel, including the kernel functional form and its parameters, is the key issu... 详细信息
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image Representation via Sub-dictionary based Sparse Coding
Image Representation via Sub-dictionary based Sparse Coding
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International Joint Conference on Neural Networks
作者: Bingxin Xu Qian Yin Ping Guo Hongzhe Liu Beijing Key Laboratory of Information Service Engineering Beijing Union University Image Processing and Pattern Recognition Laboratory Beijing Normal University
In this paper, a sub-dictionary based sparse coding method is proposed for image representation. The novel sparse coding method substitutes a new regularization item for L1-norm in the sparse representation model. The... 详细信息
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Pulsar Candidate Selection by Assembling Positive Sample Emphasized Classifiers
Pulsar Candidate Selection by Assembling Positive Sample Emp...
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International Conference on Computational Intelligence and Security
作者: Yao Yao Xin Xin Ping Guo School of Computer Science and Technology Beijing Institute of Technology Beijing China Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China
Pulsar candidate selection identifies prospective observations of modern radio pulsar surveys for further inspection in search of real pulsars. Typically, human experts visually select valuable candidates and eliminat... 详细信息
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Correction to: Internet gaming disorder: deficits in functional and structural connectivity in the ventral tegmental area-Accumbens pathway
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Brain imaging and behavior 2019年 第4期13卷 1182页
作者: Ruonan Wang Min Li Meng Zhao Dahua Yu Yu Hu Corinde E Wiers Gene-Jack Wang Nora D Volkow Kai Yuan School of Life Science and Technology Xidian University Xi'an Shaanxi 710071 People's Republic of China. Engineering Research Center of Molecular and Neuro Imaging Ministry of Education Xi'an People's Republic of China. Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing School of Information Engineering Inner Mongolia University of Science and Technology Baotou Inner Mongolia 014010 People's Republic of China. National Institute on Alcoholism and Alcohol Abuse National Institutes of Health Bethesda MD 20892 USA. National Institute on Drug Abuse National Institutes of Health Bethesda MD 20892 USA. School of Life Science and Technology Xidian University Xi'an Shaanxi 710071 People's Republic of China. kyuan@***. Engineering Research Center of Molecular and Neuro Imaging Ministry of Education Xi'an People's Republic of China. kyuan@***. Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing School of Information Engineering Inner Mongolia University of Science and Technology Baotou Inner Mongolia 014010 People's Republic of China. kyuan@***. National Institute on Alcoholism and Alcohol Abuse National Institutes of Health Bethesda MD 20892 USA. kyuan@***. Guangxi Key Laboratory of Multi-Source Information Mining and Security Guangxi Normal University Guilin People's Republic of China. kyuan@***.
The original version of this article contained mistakes, and the authors would like to correct them. The correct details are given below.
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A Pseudoinverse Incremental Algorithm for Fast Training Deep Neural Networks with Application to Spectra pattern recognition
A Pseudoinverse Incremental Algorithm for Fast Training Deep...
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International Joint Conference on Neural Networks
作者: Ke Wang Ping Guo Qian Yin A-Li Luo Xin Xin School of Computer Science and Technology Beijing Institute of Technology Image Processing and Pattern Recognition Laboratory Beijing Normal University Key Laboratory of Optical Astronomy National Astronomical Observatories Chinese Academy of Sciences
Deep learning scheme has received significant attention during these years, particularly as a way of building hierarchical representations from unlabeled data for a variety of signal and information processing tasks. ... 详细信息
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Removal of random-valued impulse noise by Khalimsky grid
Removal of random-valued impulse noise by Khalimsky grid
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Asia Pacific Conference on Multimedia and Broadcasting (APMediaCast)
作者: Hussain Dawood Hassan Dawood Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China
In this paper, based on Khalimsky grid, a new Random-valued Impulse noise identification and removal method is proposed. Khalimsky grid can presents the neighborhood relationship among the pixels in the sliding window... 详细信息
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Comparison of linear dimensionality reduction methods in image annotation
Comparison of linear dimensionality reduction methods in ima...
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International Workshop on Advanced Computational Intelligence (IWACI)
作者: Shiqiang Li Hussain Dawood Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China
Dimension reduction methods are often used to analyzing high dimensional data, linear dimension methods are commonly used due to their simple geometric interpretations and for effective computational cost. Dimension r... 详细信息
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