检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

142 篇 期刊文献
128 篇 会议

馆藏范围

270 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

139 篇 工学
- 70 篇 计算机科学与技术...
- 65 篇 电气工程
- 17 篇 信息与通信工程
- 15 篇 控制科学与工程
- 10 篇 仪器科学与技术
- 10 篇 生物医学工程（可授...
- 5 篇 测绘科学与技术
- 5 篇 软件工程
- 5 篇 生物工程
- 4 篇 机械工程
- 4 篇 交通运输工程
- 4 篇 环境科学与工程（可...
- 3 篇 电子科学与技术（可...
- 3 篇 核科学与技术
- 2 篇 土木工程
61 篇 理学
- 34 篇 统计学（可授理学、...
- 17 篇 数学
- 13 篇 生物学
- 7 篇 物理学
- 3 篇 系统科学
- 2 篇 地理学
42 篇 医学
- 22 篇 基础医学(可授医学...
- 18 篇 临床医学
- 9 篇 特种医学
13 篇 经济学
- 12 篇 应用经济学
- 2 篇 理论经济学
9 篇 农学
- 4 篇 农业资源与环境
8 篇 管理学
- 3 篇 管理科学与工程(可...
- 3 篇 工商管理
3 篇 教育学
- 3 篇 心理学(可授教育学...
1 篇 法学
1 篇 文学
1 篇 军事学
1 篇 艺术学

主题

270 篇 expectation-maxi...
45 篇 maximum likeliho...
41 篇 parameter estima...
22 篇 iterative algori...
17 篇 hidden markov mo...
17 篇 image reconstruc...
14 篇 statistics
14 篇 covariance matri...
13 篇 image segmentati...
13 篇 convergence
13 篇 estimation theor...
13 篇 algorithm design...
12 篇 gaussian distrib...
12 篇 layout
11 篇 algorithms
11 篇 maximum likeliho...
11 篇 signal processin...
11 篇 channel estimati...
11 篇 stochastic proce...
10 篇 degradation

机构

4 篇 ohio state univ ...
3 篇 department of el...
3 篇 harbin inst tech...
3 篇 ece department l...
2 篇 athens univ econ...
2 篇 communications l...
2 篇 open univ dept c...
2 篇 univ toulouse ir...
2 篇 washington unive...
2 篇 department of in...
2 篇 washington univ ...
2 篇 department of co...
2 篇 german aerosp ct...
2 篇 department of el...
2 篇 biomagnetic imag...
2 篇 department of el...
2 篇 univ calif berke...
2 篇 mit harvard mit ...
2 篇 golden metallic ...
2 篇 caltech pasadena...

作者

5 篇 snyder dl
4 篇 schniter philip
3 篇 miller mi
3 篇 wong k. c. p.
3 篇 reel parminder s...
3 篇 boerner anko
3 篇 yang xianqiang
3 篇 dooley laurence ...
2 篇 parminder singh ...
2 篇 r.l. lagendijk
2 篇 girolami m
2 篇 brown emery n.
2 篇 m. coates
2 篇 lacan jerome
2 篇 c. herzet
2 篇 l. vandendorpe
2 篇 d.e. boekee
2 篇 bayen alexandre
2 篇 j. biemond
2 篇 j. yang

语言

262 篇 英文
8 篇 其他

检索条件"主题词=Expectation-Maximization algorithms"

共 270 条记录，以下是221-230 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Research of Russian Conversion Algorithm based on Hidden Markov Model

Research of Russian Conversion Algorithm based on Hidden Mar...

引用

Image Processing, Electronics and Computers (IPEC), Asia-Pacific Conference on

作者： Yang Wang School of International Education Heilongjiang Institute of Technology JiXi China

ISBN: (数字)9798350374407

ISBN: (纸本)9798350374414

Phonetic conversion technology is pivotal in developing resources for Russian speech information processing. This paper aims to enhance the Russian phoneme set based on SAMPA, ensuring accurate reflection of stress position and vowel reduction in Russian words. Utilizing the improved phoneme set, this paper successfully constructed a Russian pronunciation dictionary with 20,000 words. A data-driven Russian phonetic conversion algorithm leveraging the Hidden Markov Model (HMM) for alignment, modeling, and decoding is proposed. Initially, the expectation-maximization algorithm aligns Russian phonetics in a “many-to-many” manner. Subsequently, alignment results are trained using a joint N-gram model and transformed into a HMM pronunciation model. The HMM decoding algorithm ultimately predicts word pronunciation accurately. Cross-validation experiments yielded satisfactory results, and they show that the proposed can be easily implemented in the computer assisted system and provide enhanced accuracy and convenience to the Russian conversion process.

关键词： Accuracy Dictionaries Transducers Computational modeling Hidden Markov models Phonetics Prediction algorithms Decoding expectation-maximization algorithms Stress

来源：评论

学校读者我要写书评

暂无评论

Hidden Markov Modeling of Noise Periodograms Using Rayleigh Mixture Models

Hidden Markov Modeling of Noise Periodograms Using Rayleigh ...

引用

Asilomar Conference on Signals, Systems & Computers

作者： K.V. Sorensen S.V. Andersen Department of Communication Technology University of Aalborg Aalborg Denmark

来源：评论

学校读者我要写书评

暂无评论

LADAR Range Image Segmentation using Curve Evolution and Maximum Likelihood Estimation

LADAR Range Image Segmentation using Curve Evolution and Max...

引用

Asilomar Conference on Signals, Systems & Computers

作者： Haihua Feng W.C. Karl D.A. Castanon MathWorks Inc. Natick MA USA ECE Department Boston University Boston MA USA

In this paper, we develop a new maximum likelihood-based, curve evolution approach for laser radar range image segmentation. This approach combines a hybrid scene model for representing the range distribution of the field and a statistical mixture model for the range data measurement noise. The image segmentation problem is formulated as an energy minimization problem which jointly estimates the target boundary together with the target region intensity and background texture directly from the noisy range data. Curve evolution techniques and an expectation-maximization algorithm are jointly employed as an efficient solver for minimizing the objective energy

关键词： Laser radar Image segmentation Maximum likelihood estimation Laser modes Laser noise Radar imaging Layout Noise measurement Background noise expectation-maximization algorithms

来源：评论

学校读者我要写书评

暂无评论

Research on Language Recognition algorithms Based on Segment-Level Features and Automatic Identification

Research on Language Recognition Algorithms Based on Segment...

引用

IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)

作者： Le Zu Yong Kang Jie Gao Shanshan He School of General Education Wannan Medical College Wuhu China

ISBN: (数字)9798350377255

ISBN: (纸本)9798350377262

Language recognition technology plays a crucial role in automated speech processing within multilingual environments, particularly under the globalized context where the increasing linguistic diversity poses higher demands on language recognition systems. Due to their robustness and efficiency, segment-level features and automatic identification algorithms have gradually become focal points of research. This paper explores a variety of language signal feature parameters, including RASTA-PLP parameters, MFCC parameters, RASTA-MFCC parameters, and CMS-MFCC parameters, as well as extraction methods for sliding difference cepstrum parameters and their applications in language recognition. Gaussian Mixture Models, along with their improved expectation-maximization algorithms and greedy expectation-maximization algorithms, are thoroughly analyzed to enhance the accuracy and robustness of language recognition. Preliminary experiments verify the performance of different feature parameters and algorithms on actual datasets, demonstrating that RASTA and CMS techniques significantly enhance the MFCC parameters.

关键词： Accuracy Training data Speech recognition Feature extraction Robustness Multilingual Mel frequency cepstral coefficient expectation-maximization algorithms Optimization Gaussian mixture model

来源：评论

学校读者我要写书评

暂无评论

Serialized Interacting Mixed Membership Stochastic Block Model

Serialized Interacting Mixed Membership Stochastic Block Mod...

引用

IEEE International Conference on Data Mining (ICDM)

作者： Gaël Poux-médard Julien Velcin Sabine Loudcher ERIC Lab Université de Lyon Lyon France

Last years have seen a regain of interest for the use of stochastic block modeling (SBM) in recommender systems. These models are seen as a flexible alternative to tensor decomposition techniques that are able to handle labeled data. Recent works proposed to tackle discrete recommendation problems via SBMs by considering larger contexts as input data and by adding second order interactions between contexts’ related elements. In this work, we show that these models are all special cases of a single global framework: the Serialized Interacting Mixed membership Stochastic Block Model (SIMSBM). It allows to model an arbitrarily large context as well as an arbitrarily high order of interactions. We demonstrate that SIMSBM generalizes several recent SBM-based baselines. Besides, we demonstrate that our formulation allows for an increased predictive power on five real-world datasets. 1

关键词： Tensors Systematics Stochastic processes Predictive models Data models Data mining expectation-maximization algorithms

来源：评论

学校读者我要写书评

暂无评论

Probabilistic Image-Based Rendering with Gaussian Mixture Model

Probabilistic Image-Based Rendering with Gaussian Mixture Mo...

引用

International Conference on Pattern Recognition

作者： Wenfeng Li Baoxin Li Department of Computer Science & Engineering Arizona State University Tempe AZ USA

ISBN: (纸本)0769525210

One major challenge in traditional image-based rendering is 3D scene reconstruction by estimating accurate dense depth map, which suffers from the ambiguities in textureless or periodically textured regions. Alternatively, statistical methods may be used to estimate a most likely color for each pixel for photorealistic rendering from multiple views of the same scene. Such statistical methods normally require a relatively large number of input images to achieve reasonable quality for the synthesized image, if the estimation is purely nonparametric. In this paper, based on some reasonable assumptions on the configuration of the multiple views, we propose to use a two-component Gaussian mixture model for the appearance of a given pixel in all the views so that both the problem of occlusion and the problem of noise can be considered simultaneously. Then we use the expectation-maximization algorithm to estimate the model parameters. The virtual pixel is given as a maximum likelihood estimate for one of the mixture components. Experiments shows that reasonable performance can be obtained even with only a few input images

关键词： Rendering (computer graphics) Layout Pixel Image reconstruction Statistical analysis expectation-maximization algorithms Parameter estimation Maximum likelihood estimation Information geometry Cameras

来源：评论

学校读者我要写书评

暂无评论

An EM algorithm for brain tumor image registration: A tumor growth modeling based approach

An EM algorithm for brain tumor image registration: A tumor ...

引用

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Ali Gooya George Biros Christos Davatzikos Section of Biomedical Image Analysis The University of Pennsylvania Georgia Institute of Technology Section of Biomedical Image Analysis The University of Pennsylvania USA

This paper investigates the problem of atlas registration of brain images with tumors. Multi-parametric imaging modalities are first utilized for segmentations of different tissues, and to compute the posterior probability map (PBM) of membership to each tissue class, using supervised learning. Similar maps are generated in the initially normal atlas, by modeling the tumor growth. An expectation-maximization algorithm is used to estimate the spatial transformation and other parameters related to tumor simulation are optimized through Asynchronous Parallel Pattern Search (APPSPACK). The proposed method has been evaluated on simulated data sets created by Statistically Simulated Deformations (SSD), and real multichannel Glioma data sets. The performance has been evaluated both quantitatively and qualitatively. The results show that our method is promising to achieve a good similarity between the warped templates and patient images.

关键词： Neoplasms Image registration Brain modeling Deformable models Biomedical imaging Image analysis Algorithm design and analysis expectation-maximization algorithms Pathology Image segmentation

来源：评论

学校读者我要写书评

暂无评论

PTZ camera network reconfiguration

PTZ camera network reconfiguration

引用

ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC

作者： C. Piciarelli C. Micheloni G.L. Foresti University of Udine Udine Italy

Vision network based surveillance systems are more and more common in public places. Typically, a mixture of static and pan-tilt-zoom (PTZ) cameras is used. Modern systems task PTZ cameras as a consequence of particular events needing further investigation; anyhow, the configuration of the network can be considered fixed and determined at the moment of deployment. In this work, we deal with a problem that has not yet been widely addressed: how a network can automatically change its configuration to enhance the monitoring capabilities. In particular, we propose a novel network reconfiguration algorithm that, given a map of activities, configures the pan, tilt and zoom parameters of all the cameras in order to improve the detection. A spherical model to project all the activities in the monitored area with respect to the optical centre of each camera is introduced. Such a model leads to an optimization problem that can be solved by means of the expectation-maximization algorithm and whose solutions are the new pan, tilt and zoom values for each PTZ camera. Experimental results will be proposed with both synthetic and real data to show how the proposed algorithm can be applied to different cases.

关键词： Cameras Layout Infrared sensors Dynamic programming Surveillance Computerized monitoring Change detection algorithms Optical sensors expectation-maximization algorithms Computer vision

来源：评论

学校读者我要写书评

暂无评论

Scintillation Time Series Synthesis for Satellite Links with Hidden Markov Model

Scintillation Time Series Synthesis for Satellite Links with...

引用

International Workshop on Satellite and Space Communications (IWSSC)

作者： Laszlo Csurgai-Horvath Janos Bito Department of Broadband Infocommunications and Electromagnetic Theory Budapest University슠of슠Technology슠and슠Economics Budapest Hungary

This paper introduces a method to model the rapid attenuation fluctuations (the scintillation) on satellite links with generating the time series of attenuation levels. The applied model is a hidden Markov model which is parameterized from an appropriate filtered Gaussian white noise signal. For the parameterization of the Markov chain the Baum-Welch expectation-maximization algorithm has been used. The resulting Markov model is applicable to generate scintillation time series for any desired duration with the time and amplitude resolution of the original training data. From the synthesized time series the statistical properties like the cumulative distribution and the dynamics of the scintillation can be also determined. To prove the accuracy of the model at first the cumulative distribution function of the original and synthesized time series are compared. A further test of the model validity is the comparison with real scintillation measurement on a land mobile satellite link. Finally, the spectral test of the filtered Gaussian model, the hidden Markov model and the satellite link measurement shows that the constant and decreasing parts in the periodograms are showing similarities what confirms the good quality of the model.

关键词： Satellites Hidden Markov models Signal synthesis Attenuation Testing Fluctuations White noise expectation-maximization algorithms Signal resolution Training data

来源：评论

学校读者我要写书评

暂无评论

Minimum classification error factor analysis (MCE-FA) for automatic speech recognition

Minimum classification error factor analysis (MCE-FA) for au...

引用

IEEE Workshop on Automatic Speech Recognition and Understanding

作者： M. Rahim L. Saul AT and T Research Laboratories Florham Park NJ USA

Modeling acoustic correlation in automatic speech recognition systems is essential when the speech signal is non stationary or corrupted by noise. We present a statistical method for improved acoustic modeling in continuous density hidden Markov models (HMMs). Factor analysis uses a small number of parameters to model the covariance structure of the speech signal. These parameters are estimated by an expectation-maximization algorithm, then further adjusted using discriminative minimum classification error training. Experimental results on 1219 New Jersey town names demonstrate that the proposed method produces faster, smaller and more accurate recognition models.

关键词： Error analysis Hidden Markov models Speech analysis Automatic speech recognition Speech enhancement Acoustic noise Statistical analysis Signal analysis Parameter estimation expectation-maximization algorithms

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共27页 << < 18 19 20 21 22 23 24 25 26 27 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：