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

1,638 篇 会议
26 篇 期刊文献
3 册 图书

馆藏范围

1,667 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,172 篇 工学
- 833 篇 电气工程
- 703 篇 计算机科学与技术...
- 256 篇 信息与通信工程
- 154 篇 软件工程
- 90 篇 控制科学与工程
- 78 篇 仪器科学与技术
- 54 篇 生物医学工程（可授...
- 47 篇 电子科学与技术（可...
- 37 篇 生物工程
- 23 篇 机械工程
- 22 篇 光学工程
- 6 篇 动力工程及工程热...
- 5 篇 建筑学
- 5 篇 土木工程
- 5 篇 测绘科学与技术
- 4 篇 材料科学与工程（可...
316 篇 理学
- 162 篇 物理学
- 94 篇 数学
- 60 篇 系统科学
- 48 篇 统计学（可授理学、...
- 41 篇 生物学
89 篇 医学
- 67 篇 临床医学
- 26 篇 基础医学(可授医学...
- 12 篇 药学(可授医学、理...
- 7 篇 医学技术（可授医学...
49 篇 管理学
- 32 篇 图书情报与档案管...
- 15 篇 管理科学与工程(可...
- 6 篇 工商管理
9 篇 农学
- 9 篇 作物学
8 篇 法学
- 7 篇 社会学
3 篇 教育学
2 篇 经济学

主题

332 篇 machine learning
182 篇 signal processin...
154 篇 deep learning
142 篇 signal processin...
142 篇 training
113 篇 estimation
87 篇 feature extracti...
72 篇 field programmab...
71 篇 modulation
68 篇 ofdm
68 篇 clocks
68 篇 filtration
63 篇 neural networks
63 篇 optimization
60 篇 conferences
48 篇 data models
47 篇 computational mo...
47 篇 kernel
47 篇 machine learning...
46 篇 support vector m...

机构

11 篇 ieee
7 篇 southeast univ n...
6 篇 natl chiao tung ...
6 篇 oregon state uni...
5 篇 korea univ dept ...
5 篇 mila quebec ai i...
5 篇 middle east tech...
4 篇 georgia inst tec...
4 篇 princeton univ p...
4 篇 georgia inst tec...
4 篇 acad sinica res ...
4 篇 aalborg univ dep...
4 篇 yale univ dept g...
4 篇 aristotle univ t...
4 篇 univ cent florid...
4 篇 department of el...
4 篇 univ oulu ctr ma...
4 篇 purple mountain ...
4 篇 imperial coll lo...
4 篇 nanyang technol ...

作者

12 篇 chien jen-tzung
8 篇 simeone osvaldo
8 篇 tefas anastasios
7 篇 jenssen robert
7 篇 erdogmus deniz
7 篇 wang wenwu
7 篇 larsen jan
7 篇 anastasios tefas
7 篇 raich raviv
7 篇 principe jose c.
7 篇 passalis nikolao...
7 篇 hansen lars kai
6 篇 sarkka simo
6 篇 nikolaos passali...
6 篇 sayed ali h.
6 篇 plumbley mark d.
5 篇 shi qingjiang
5 篇 jen-tzung chien
5 篇 sharon gannot
5 篇 vural elif

语言

1,651 篇 英文
12 篇 中文
3 篇 其他
1 篇 土耳其文

检索条件"任意字段=2017 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2017"

共 1667 条记录，以下是51-60 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：

COVARIATE SHIFT APPROACH FOR INVARIANT TEXTURE CLASSIFICATION

COVARIATE SHIFT APPROACH FOR INVARIANT TEXTURE CLASSIFICATIO...

引用

23rd ieee international workshop on machine learning for signal processing (mlsp)

作者： Hassan, Ali Shaukat, Arslan NUST Coll Elect & Mech Engn Dept Comp Engn Islamabad Pakistan

ISBN: (纸本)9781479911806

This paper deals with rotation and scale invariant texture classification problem at the machine learning level by modelling these variations in the texture data as a covariate shift. Covariate shift between the training and testing data is minimised by estimating importance weights for the training data which are then incorporated in a standard machine learning algorithm like support vector machines. The effectiveness of these importance weighted support vector machines (IW-SVM) are tested on the Brodatz dataset. The comparative classification results with several other state of the art methodologies demonstrate the effectiveness of the proposed covariate shift approach for rotation and scale invariant texture classification.

关键词： machine learning covariate shift importance weighting and support vector machines

来源：评论

学校读者我要写书评

暂无评论

learning AND STORING THE PARTS OF OBJECTS: IMF 24

LEARNING AND STORING THE PARTS OF OBJECTS: IMF

引用

ieee international workshop on machine learning for signal processing (mlsp)

作者： de Frein, Ruairi Telecommun Software & Syst Grp Waterford Ireland

ISBN: (纸本)9781479936946

A central concern for many learning algorithms is how to efficiently store what the algorithm has learned. An algorithm for the compression of Nonnegative Matrix Factorizations is presented. Compression is achieved by embedding the factorization in an encoding routine. Its performance is investigated using two standard test images, Peppers and Barbara. The compression ratio (18:1) achieved by the proposed Matrix Factorization improves the storage-ability of Nonnegative Matrix Factorizations without significantly degrading accuracy (approximate to 1-3dB degradation is introduced). We learn as before, but storage is cheaper.

关键词： matrix factorization compression

来源：评论

学校读者我要写书评

暂无评论

DICTIONARY learning FOR PITCH ESTIMATION IN SPEECH signalS

DICTIONARY LEARNING FOR PITCH ESTIMATION IN SPEECH SIGNALS

引用

27th ieee international workshop on machine learning for signal processing (mlsp)

作者： Huang, Feng Balazs, Peter Austrian Acad Sci Acoust Res Inst Vienna Austria

ISBN: (纸本)9781509063413

This paper presents an automatic approach for parameter training for a sparsity-based pitch estimation method that has been previously published. For this pitch estimation method, the harmonic dictionary is a key parameter that needs to be carefully prepared beforehand. In the original method, extensive human supervision and involvement are required to construct and label the dictionary. In this study, we propose to employ dictionary learning algorithms to learn the dictionary directly from training data. We apply and compare 3 typical dictionary learning algorithms, i.e., the method of optimized directions (MOD), K-SVD and online dictionary learning (ODL), and propose a post-processing method to label and adapt a learned dictionary for pitch estimation. Results show that MOD and properly initialized ODL (pi-ODL) can lead to dictionaries that exhibit the desired harmonic structures for pitch estimation, and the post-processing method can significantly improve performance of the learned dictionaries in pitch estimation. The dictionary obtained with pi-ODL and post-processing attained pitch estimation accuracy close to the optimal performance of the manual dictionary. It is positively shown that dictionary learning is feasible and promising for this application.

关键词： Pitch estimation sparsity harmonic structure dictionary learning dictionary post-processing

来源：评论

学校读者我要写书评

暂无评论

MULTINOMIAL SAMPLING FOR HIERARCHICAL CHANGE-POINT DETECTION 30

MULTINOMIAL SAMPLING FOR HIERARCHICAL CHANGE-POINT DETECTION

引用

30th ieee international workshop on machine learning for signal processing (mlsp)

作者： Romero-Medrano, Lorena Moreno-Munoz, Pablo Artes-Rodriguez, Antonio Univ Carlos III Madrid Dept Signal Theory & Commun Madrid Spain Gregorio Maranon Hlth Res Inst Madrid Spain

ISBN: (纸本)9781728166629

Bayesian change-point detection, together with latent variable models, allows to perform segmentation over high-dimensional time-series. We assume that change-points lie on a lower-dimensional manifold where we aim to infer subsets of discrete latent variables. For this model, full inference is computationally unfeasible and pseudo-observations based on pointestimates are used instead. However, if estimation is not certain enough, change-point detection gets affected. To circumvent this problem, we propose a multinomial sampling methodology that improves the detection rate and reduces the delay while keeping complexity stable and inference analytically tractable. Our experiments show results that outperform the baseline method and we also provide an example oriented to a human behavior study.

关键词： Bayesian inference change-point detection (CPD) latent variable models multinomial likelihoods

来源：评论

学校读者我要写书评

暂无评论

machine learning AS DIGITAL THERAPY ASSESSMENT FOR MOBILE GAIT REHABILITATION 28

MACHINE LEARNING AS DIGITAL THERAPY ASSESSMENT FOR MOBILE GA...

引用

ieee 28th international workshop on machine learning for signal processing (mlsp)

作者： Alcaraz, Javier Conte Moghaddamnia, Sanam Poschadel, Nils Peissig, Juergen Leibniz Univ Hannover Inst Commun Technol Hannover Germany

ISBN: (纸本)9781538654774

A novel real-time acoustic feedback (RTAF) based on machine learning to reduce the duration and to improve the progress in the rehabilitation is presented. Wearable technology (WT) has emerged as a viable means to provide low-cost digital healthcare and therapy course outside the medical environment like hospitals and clinics. In this paper we show that the RTAF together with WTs can offer an excellent solution to be used in rehabilitation. The method of RTAF based on machine learning as well as a study for proving its effectiveness are presented below. The results show a faster recovery time using RTAF. The proposed RTAF shows a great potential to be used and deployed to support digital healthcare, therapy and rehabilitation.

关键词： machine learning Real-Time Wearable Technology Rehabilitation Android Acoustic Feedback Gait

来源：评论

学校读者我要写书评

暂无评论

A RECURRENT ENCODER-DECODER APPROACH WITH SKIP-FILTERING CONNECTIONS FOR MONAURAL SINGING VOICE SEPARATION

A RECURRENT ENCODER-DECODER APPROACH WITH SKIP-FILTERING CON...

引用

27th ieee international workshop on machine learning for signal processing (mlsp)

作者： Mimilakis, Stylianos Ioannis Drossos, Konstantinos Virtanen, Tuomas Schuller, Gerald Fraunhofer IDMT Ilmenau Germany Tampere Univ Technol Tampere Finland Tech Univ Ilmenau Ilmenau Germany

ISBN: (纸本)9781509063413

The objective of deep learning methods based on encoder-decoder architectures for music source separation is to approximate either ideal time-frequency masks or spectral representations of the target music source(s). The spectral representations are then used to derive time-frequency masks. In this work we introduce a method to directly learn time-frequency masks from an observed mixture magnitude spectrum. We employ recurrent neural networks and train them using prior knowledge only for the magnitude spectrum of the target source. To assess the performance of the proposed method, we focus on the task of singing voice separation. The results from an objective evaluation show that our proposed method provides comparable results to deep learning based methods which operate over complicated signal representations. Compared to previous methods that approximate time-frequency masks, our method has increased performance of signal to distortion ratio by an average of 3.8 dB.

关键词： Music source separation deep learning denoising

来源：评论

学校读者我要写书评

暂无评论

MIXTURE WEIGHT INFLUENCE ON KERNEL ENTROPY COMPONENT ANALYSIS AND SEMI-SUPERVISED learning USING THE LASSO

MIXTURE WEIGHT INFLUENCE ON KERNEL ENTROPY COMPONENT ANALYSI...

引用

22nd ieee international workshop on machine learning for signal processing (mlsp)

作者： Myhre, Jonas Nordhaug Jenssen, Robert Univ Tromso Dept Phys & Technol N-9001 Tromso Norway

ISBN: (纸本)9781467310260

The aim of this paper is two-fold. First, we show that the newly developed spectral method known as kernel entropy component analysis (kernel ECA) captures cluster structure, which is very important in semi-supervised learning, and we provide an analysis showing how mixture weights influence kernel ECA in a mixture of cluster components setting. Second, we develop a semi-supervised kernel ECA classifier based on the Lasso framework, and report promising results compared to the state-of-the art.

关键词： Spectral dimensionality reduction Semi-supervised learning Kernel entropy component analysis Cluster assumption Mixture densities Lasso Data spectroscopy

来源：评论

学校读者我要写书评

暂无评论

learning EMBEDDINGS FOR SPEAKER CLUSTERING BASED ON VOICE EQUALITY

LEARNING EMBEDDINGS FOR SPEAKER CLUSTERING BASED ON VOICE EQ...

引用

27th ieee international workshop on machine learning for signal processing (mlsp)

作者： Lukic, Yanick X. Vogt, Carlo Duerr, Oliver Stadelmann, Thilo Zurich Univ Appl Sci Winterthur Switzerland

ISBN: (纸本)9781509063413

Recent work has shown that convolutional neural networks (CNNs) trained in a supervised fashion for speaker identification are able to extract features from spectrograms which can be used for speaker clustering. These features are represented by the activations of a certain hidden layer and are called embeddings. However, previous approaches require plenty of additional speaker data to learn the embedding, and although the clustering results are then on par with more traditional approaches using MFCC features etc., room for improvements stems from the fact that these embeddings are trained with a surrogate task that is rather far away from segregating unknown voices - namely, identifying few specific speakers. We address both problems by training a CNN to extract embeddings that are similar for equal speakers (regardless of their specific identity) using weakly labeled data. We demonstrate our approach on the well-known TIMIT dataset that has often been used for speaker clustering experiments in the past. We exceed the clustering performance of all previous approaches, but require just 100 instead of 590 unrelated speakers to learn an embedding suited for clustering.

关键词： Speaker Clustering Speaker Recognition Convolutional Neural Network Speaker Embedding

来源：评论

学校读者我要写书评

暂无评论

QUADRATIC MUTUAL INFORMATION REGULARIZATION IN REAL-TIME DEEP CNN MODELS 30

QUADRATIC MUTUAL INFORMATION REGULARIZATION IN REAL-TIME DEE...

引用

30th ieee international workshop on machine learning for signal processing (mlsp)

作者： Tzelepi, Maria Tefas, Anastasios Aristotle Univ Thessaloniki Dept Informat Thessaloniki Greece

ISBN: (纸本)9781728166629

In this paper, regularized lightweight deep convolutional neural network models, capable of effectively operating in realtime on devices with restricted computational power for highresolution video input are proposed. Furthermore, a novel regularization method motivated by the Quadratic Mutual Information, in order to improve the generalization ability of the utilized models is proposed. Extensive experiments on various binary classification problems involved in autonomous systems are performed, indicating the effectiveness of the proposed models as well as of the proposed regularizer.

关键词： Quadratic Mutual Information Regularizer Lightweight Models Real-time Deep learning

来源：评论

学校读者我要写书评

暂无评论

REDUNDANT TIME-FREQUENCY MARGINALS FOR CHIRPLET DECOMPOSITION

REDUNDANT TIME-FREQUENCY MARGINALS FOR CHIRPLET DECOMPOSITIO...

引用

22nd ieee international workshop on machine learning for signal processing (mlsp)

作者： Weruaga, Luis Khalifa Univ Sharjah U Arab Emirates

ISBN: (纸本)9781467310260

This paper presents the foundations of a novel method for chirplet signal decomposition. In contrast to basis-pursuit techniques on over-complete dictionaries, the proposed method uses a reduced set of adaptive parametric chirplets. The estimation criterion corresponds to the maximization of the likelihood of the chirplet parameters from redundant time-frequency marginals. The optimization algorithm that results from this scenario combines Gaussian mixture models and Huber's robust regression in an iterative fashion. Simulation results support the proposed avenue.

关键词： Complex Gaussian chirplet sparse signal decomposition maximum likelihood

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167页 << < 2 3 4 5 6 7 8 9 10 11 > >>

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：