机构

• 长春光学精密机械与物... [2]
• 自动化研究所 [2]
• 沈阳自动化研究所 [1]
• 软件研究所 [1]

采集方式

• OAI收割 [6]

内容类型

• 期刊论文 [4]
• 会议论文 [2]

发表日期

• 2020 [1]
• 2018 [1]
• 2008 [1]
• 2006 [3]

学科主题

• Computer S... [1]
• Electrical... [1]
• Hardware &... [1]
• Theory & ... [1]

筛选

浏览/检索结果: 共6条，第1-6条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Item Response Theory Based Ensemble in Machine Learning 期刊论文  OAI收割 International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 5, 页码: 621-636 作者:  Ziheng Chen;  Hongshik Ahn   |  收藏  |  浏览/下载：30/0  |  提交时间：2021/02/22 Classification  ensemble learning  item response theory  machine learning  expectation maximization (EM) algorithm.   A Generalized Model for Robust Tensor Factorization With Noise Modeling by Mixture of Gaussians 期刊论文  OAI收割 IEEE Transactions on Neural Networks and Learning Systems, 2018 作者:  Wang Y(王尧);  Han Z(韩志);  Lin, Lin;  Tang YD(唐延东);  Chen XA(陈希爱)   |  收藏  |  浏览/下载：55/0  |  提交时间：2018/03/25 Expectation–maximization (EM) algorithm  generalized weighted low-rank tensor factorization (GWLRTF)  mixture of Gaussians (MoG) model  tensor factorization   Contour extracting with combination particle filtering and em algorithm (EI CONFERENCE) 会议论文  OAI收割 International Symposium on Photoelectronic Detection and Imaging, ISPDI 2007: Related Technologies and Applications, September 9, 2007 - September 12, 2007, Beijing, China Meng B.; Zhu M. 收藏  |  浏览/下载：26/0  |  提交时间：2013/03/25 The problem of extracting continuous structures from images is a difficult issue in early pattern recognition and image processings[1]. Tracking with contours in a filtering framework requires a dynamical model for prediction. Recently  Particle filter  is widely used because its multiple hypotheses and versatility within framework. However  the good choice of the propagation function is still its main problem. In this paper  an improved particle filter  EM-PF algorithm is proposed which using the EM (Expectation-Maximization) algorithm to learn the dynamical models. The EM algorithm can explicitly learn the parameters of the dynamical models from training sequences. The advantage of using the EM algorithm in particle filter is that it is capable of improve tracking contour by having accurate model parameters. Though the experiment results  we show how our EM-PF can be applied to produces more robust and accurate extracting.   Spatially variant mixture multiscale autoregressive Modeling of SAR imagery for unsupervised segmentation 期刊论文  OAI收割 CHINESE JOURNAL OF ELECTRONICS, 2006, 卷号: 15, 期号: 2, 页码: 359-362 作者:  Ju, YW;  Tian, Z 收藏  |  浏览/下载：26/0  |  提交时间：2015/11/07 spatially variant mixture multiscale autoregressive model  least square estimation  EM (expectation maximization) algorithm  unsupervised segmentation  SAR (synthetic aperture radar) imagery   CR image filter methods research based on wavelet-domain hidden markov models (EI CONFERENCE) 会议论文  OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者:  Wang J.-L.;  Wang J.-L.;  Li D.-Y.;  Wang Y.-P. 收藏  |  浏览/下载：18/0  |  提交时间：2013/03/25 In the procedure of computed radiography imaging  we should firstly get across the characters of kinds of noises and the relationship between the image signals and noises. Based on the specialties of computed radiography (CR) images and medical image processing  we have study the filtering methods for computed radiography images noises. On the base of analyzing computed radiography imaging system in detail  the author think that the major two noises are Gaussian white noise and Poisson noise. Then  the different relationship of between two kinds of noises and signal were studied completely. By considering both the characteristics of computed radiography images and the statistical features of wavelet transformed images  a multiscale image filtering algorithm  which based on two-state hidden markov model (HMM) and mixture Gaussian statistical model  has been used to decrease the Gaussian white noise in computed images. By using EM (Expectation Maximization) algorithm to estimate noise coefficients in each scale and obtain power spectrum matrix  then this carried through the syncretized two Filter that are IIR(infinite impulse response) Wiener Filter and HMM  according to scale size  and achieve the experiments as well as the comparison with other denoising methods were presented at last.   a general model for long-tailed network traffic approximation 期刊论文  OAI收割 JOURNAL OF SUPERCOMPUTING, 2006, 卷号: 38, 期号: 2, 页码: 155-172 Wang Junfeng; Zhou Hongxia; Zhou Mingtian; Li Lei   |  收藏  |  浏览/下载：19/0  |  提交时间：2011/07/13 聚类分析  区域差异  石河子network measurements  hyper-erlang distribution  network traffic  queueing analysis  expectation maximization (EM) algorithm