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

74 篇 会议
18 篇 期刊文献

馆藏范围

92 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

63 篇 工学
- 41 篇 计算机科学与技术...
- 38 篇 软件工程
- 16 篇 生物工程
- 12 篇 生物医学工程（可授...
- 10 篇 机械工程
- 9 篇 信息与通信工程
- 5 篇 电子科学与技术（可...
- 5 篇 控制科学与工程
- 4 篇 仪器科学与技术
- 3 篇 电气工程
- 2 篇 动力工程及工程热...
- 2 篇 安全科学与工程
- 1 篇 光学工程
- 1 篇 化学工程与技术
32 篇 理学
- 22 篇 数学
- 14 篇 生物学
- 8 篇 统计学（可授理学、...
- 3 篇 物理学
- 3 篇 系统科学
- 1 篇 化学
17 篇 管理学
- 8 篇 管理科学与工程(可...
- 8 篇 图书情报与档案管...
- 3 篇 工商管理
6 篇 医学
- 6 篇 临床医学
- 5 篇 基础医学(可授医学...
- 3 篇 公共卫生与预防医...
- 3 篇 药学(可授医学、理...
3 篇 法学
- 3 篇 社会学
2 篇 农学
- 2 篇 作物学
1 篇 经济学
- 1 篇 应用经济学
1 篇 艺术学

主题

12 篇 data models
8 篇 feature extracti...
7 篇 computational mo...
7 篇 bayes methods
6 篇 ubiquitous compu...
5 篇 autism
4 篇 bluetooth
4 篇 optimization
4 篇 media
4 篇 blogs
4 篇 entropy
4 篇 diseases
3 篇 indexes
3 篇 hidden markov mo...
3 篇 cameras
3 篇 pragmatics
3 篇 data mining
3 篇 monitoring
3 篇 electrocardiogra...
3 篇 predictive model...

机构

36 篇 centre for patte...
21 篇 centre for patte...
5 篇 centre for patte...
3 篇 institute for fr...
3 篇 department of el...
3 篇 centre for patte...
2 篇 centre for patte...
2 篇 department of co...
2 篇 centre of patter...
2 篇 national ict aus...
2 篇 deakin universit...
2 篇 centre of patter...
2 篇 computer science...
2 篇 computer science...
1 篇 pattern recognit...
1 篇 department of ra...
1 篇 public health un...
1 篇 department of ph...
1 篇 department of in...
1 篇 centre of patter...

作者

32 篇 venkatesh svetha
26 篇 phung dinh
26 篇 svetha venkatesh
24 篇 dinh phung
10 篇 gupta sunil
10 篇 sunil gupta
9 篇 tran truyen
9 篇 rana santu
8 篇 santu rana
7 篇 nguyen tu dinh
6 篇 le trung
6 篇 vu nguyen
6 篇 nguyen thuong
5 篇 ognjen arandjelo...
5 篇 thuong nguyen
5 篇 nguyen thin
4 篇 nguyen vu
4 篇 chandan karmakar
4 篇 bo dao
4 篇 luo wei

语言

92 篇 英文

检索条件"机构=the centre for Pattern Recognition and Data Analytics"

共 92 条记录，以下是81-90 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：

Computer simulation based parameter selection for resistance exercise

Computer simulation based parameter selection for resistance...

引用

24th IASTED International Conference on Modelling and Simulation, MS 2013

作者： Arandjelović, Ognjen Centre for Pattern Recognition and Data Analytics Deakin University Geelong 3216 VIC Australia

ISBN: (纸本)9780889869561

In contrast to most scientific disciplines, sports science research has been characterized by comparatively little effort investment in the development of relevant phenomenologi-cal models. Scarcer yet is the application of said models in practice. We present a framework which allows resistance training practitioners to employ a recently proposed neu-romuscular model in actual training program design. The first novelty concerns the monitoring aspect of coaching. A method for extracting training performance characteristics from loosely constrained video sequences, effortlessly and with minimal human input, using computer vision is described. The extracted data is subsequently used to fit the underlying neuromuscular model. This is achieved by solving an inverse dynamics problem corresponding to a particular exercise. Lastly, a computer simulation of hypothetical training bouts, using athlete-specific capability parameters, is used to predict the effected adaptation and changes in performance. The software described here allows the practitioner to manipulate hypothetical training parameters and immediately see their effect on predicted adaptation for a specific athlete. Thus, this work presents a holistic view of the monitoring-assessment-adjustment loop.

关键词： Sports

来源：评论

学校读者我要写书评

暂无评论

Extraction of Latent patterns and Contexts from Social Honest Signals Using Hierarchical Dirichlet Processes

Extraction of Latent Patterns and Contexts from Social Hones...

引用

IEEE International Conference on Pervasive Computing and Communications

作者： Thuong Nguyen Dinh Phung Sunil Gupta S. Venkatesh Centre for Pattern Recognition and Data Analytics Deakin University

ISBN: (纸本)9781467345736

A fundamental task in pervasive computing is reliable acquisition of contexts from sensor data. This is crucial to the operation of smart pervasive systems and services so that they might behave efficiently and appropriately upon a given context. Simple forms of context can often be extracted directly from raw data. Equally important, or more, is the hidden context and pattern buried inside the data, which is more challenging to discover. Most of existing approaches borrow methods and techniques from machine learning, dominantly employ parametric unsupervised learning and clustering techniques. Being parametric, a severe drawback of these methods is the requirement to specify the number of latent patterns in advance. In this paper, we explore the use of Bayesian nonparametric methods, a recent data modelling framework in machine learning, to infer latent patterns from sensor data acquired in a pervasive setting. Under this formalism, nonparametric prior distributions are used for data generative process, and thus, they allow the number of latent patterns to be learned automatically and grow with the data - as more data comes in, the model complexity can grow to explain new and unseen patterns. In particular, we make use of the hierarchical Dirichlet processes (HDP) to infer atomic activities and interaction patterns from honest signals collected from sociometric badges. We show how data from these sensors can be represented and learned with HDP. We illustrate insights into atomic patterns learned by the model and use them to achieve high-performance clustering. We also demonstrate the framework on the popular Reality Mining dataset, illustrating the ability of the model to automatically infer typical social groups in this dataset. Finally, our framework is generic and applicable to a much wider range of problems in pervasive computing where one needs to infer high-level, latent patterns and contexts from sensor data.

关键词： Sensor data Ubiquitous computing HIGH DELTA PRESSURE Frameworks AUTOMATIC

来源：评论

学校读者我要写书评

暂无评论

Discriminative k-Means Clustering

Discriminative k-Means Clustering

引用

International Joint Conference on Neural Networks

作者： Ognjen Arandjelovi? Centre for Pattern Recognition and Data Analytics at Deakin University.

ISBN: (纸本)9781467361279

The k-means algorithm is a partitional clustering method. Over 60 years old, it has been successfully used for a variety of problems. The popularity of k-means is in large part a consequence of its simplicity and efficiency. In this paper we are inspired by these appealing properties of k-means in the development of a clustering algorithm which accepts the notion of "positively" and "negatively" labelled data. The goal is to discover the cluster structure of both positive and negative data in a manner which allows for the discrimination between the two sets. The usefulness of this idea is demonstrated practically on the problem of face recognition, where the task of learning the scope of a person's appearance should be done in a manner which allows this face to be differentiated from others.

关键词： variety problems k-means

来源：评论

学校读者我要写书评

暂无评论

Interactive browsing system for anomaly video surveillance

Interactive browsing system for anomaly video surveillance

引用

Intelligent Sensors, Sensor Networks and Information Processing Conference (ISSNIP)

作者： Tien-Vu Nguyen Dinh Phung Sunil Gupta Svetha Venkatesh Centre for Pattern Recognition and Data Analytics (PRaDA) Deakin University Australia

Existing anomaly detection methods in video surveillance exhibit lack of congruence between rare events detected by algorithms and what is considered anomalous by users. This paper introduces a novel browsing model to address this issue, allowing users to interactively examine rare events in an intuitive manner. Introducing a novel way to compute rare motion patterns, we estimate latent factors of foreground motion patterns through Bayesian Nonparametric Factor analysis. Each factor corresponds to a typical motion pattern. A rarity score for each factor is computed, and ordered in decreasing order of rarity, permitting users to browse events using any proportion of rare factors. Rare events correspond to frames that contain the rare factors chosen. We present the user with an interface to inspect events that incorporate these rarest factors in a spatial-temporal manner. We demonstrate the system on a public video data set, showing key aspects of the browsing paradigm.

关键词： Robustness Principal component analysis Feature extraction Matrix decomposition Cameras data models Hidden Markov models

来源：评论

学校读者我要写书评

暂无评论

Making the most of the self-quotient image in face recognition

Making the most of the self-quotient image in face recogniti...

引用

International Conference on Automatic Face and Gesture recognition

作者： Ognjen Arandjelović Centre for Pattern Recognition and Data Analytics Deakin University Geelong VIC Australia

ISBN: (纸本)9781467355452

The self-quotient image is a biologically inspired representation which has been proposed as an illumination invariant feature for automatic face recognition. Owing to the lack of strong domain specific assumptions underlying this representation, it can be readily extracted from raw images irrespective of the persons's pose, facial expression etc. What makes the self-quotient image additionally attractive is that it can be computed quickly and in a closed form using simple low-level image operations. However, it is generally accepted that the self-quotient is insufficiently robust to large illumination changes which is why it is mainly used in applications in which low precision is an acceptable compromise for high recall (e.g. retrieval systems). Yet, in this paper we demonstrate that the performance of this representation in challenging illuminations has been greatly underestimated. We show that its error rate can be reduced by over an order of magnitude, without any changes to the representation itself. Rather, we focus on the manner in which the dissimilarity between two self-quotient images is computed. By modelling the dominant sources of noise affecting the representation, we propose and evaluate a series of different dissimilarity measures, the best of which reduces the initial error rate of 63.0% down to only 5.7% on the notoriously challenging YaleB data set.

关键词： Noise Lighting Face Face recognition Robustness Quantization (signal) Error analysis

来源：评论

学校读者我要写书评

暂无评论

Exploiting side information in distance dependent Chinese restaurant processes for data clustering

Exploiting side information in distance dependent Chinese re...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Cheng Li Dinh Phung Santu Rana Svetha Venkatesh Centre for Pattern Recognition and Data Analytics (PRaDA) Deakin University Geelong Australia

ISBN: (纸本)9781479900145

Multimedia contents often possess weakly annotated data such as tags, links and interactions. The weakly annotated data is called side information. It is the auxiliary information of data and provides hints for exploring the link structure of data. Most clustering algorithms utilize pure data for clustering. A model that combines pure data and side information, such as images and tags, documents and keywords, can perform better at understanding the underlying structure of data. We demonstrate how to incorporate different types of side information into a recently proposed Bayesian nonparametric model, the distance dependent Chinese restaurant process (DD-CRP). Our algorithm embeds the affinity of this information into the decay function of the DD-CRP when side information is in the form of subsets of discrete labels. It is flexible to measure distance based on arbitrary side information instead of only the spatial layout or time stamp of observations. At the same time, for noisy and incomplete side information, we set the decay function so that the DD-CRP reduces to the traditional Chinese restaurant process, thus not inducing side effects of noisy and incomplete side information. Experimental evaluations on two real-world datasets NUS WIDE and 20 Newsgroups show exploiting side information in DD-CRP significantly improves the clustering performance.

关键词： Clustering algorithms Noise measurement Mutual information Bayes methods Multimedia communication Time measurement Layout

来源：评论

学校读者我要写书评

暂无评论

A nonparametric Bayesian Poisson gamma model for count data

A nonparametric Bayesian Poisson gamma model for count data

引用

21st International Conference on pattern recognition, ICPR 2012

作者： Gupta, Sunil Kumar Phung, Dinh Venkatesh, Svetha Centre for Pattern Recognition and Data Analytics Deakin University Australia

ISBN: (纸本)9784990644109

We propose a nonparametric Bayesian, linear Poisson gamma model for count data and use it for dictionary learning. A key property of this model is that it captures the parts-based representation similar to nonnegative matrix factorization. We present an auxiliary variable Gibbs sampler, which turns the intractable inference into a tractable one. Combining this inference procedure with the slice sampler of Indian buffet process, we show that our model can learn the number of factors automatically. Using synthetic and real-world datasets, we show that the proposed model outperforms other state-of-the-art nonparametric factor models. © 2012 ICPR Org Committee.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Matching objects across the textured-smooth continuum

Matching objects across the textured-smooth continuum

引用

2012 Australasian Conference on Robotics and Automation, ACRA 2012

作者： Arandjelović, Ognjen Centre for Pattern Recognition and Data Analytics Deakin University Geelong VIC 3220 Australia

ISBN: (纸本)9780980740431

The problem of 3D object recognition is of immense practical importance, with the last decade witnessing a number of breakthroughs in the state of the art. Most of the previous work has focused on the matching of textured objects using local appearance descriptors extracted around salient image points. The recently proposed bag of boundaries method was the first to address directly the problem of matching smooth objects using boundary features. However, no previous work has attempted to achieve a holistic treatment of the problem by jointly using textural and shape features which is what we describe herein. Due to the complementarity of the two modalities, we fuse the corresponding matching scores and learn their relative weighting in a data specific manner by optimizing discriminative performance on synthetically distorted data. For the textural description of an object we adopt a representation in the form of a histogram of SIFT based visual words. Similarly the apparent shape of an object is represented by a histogram of discretized features capturing local shape. On a large public database of a diverse set of objects, the proposed method is shown to outperform significantly both purely textural and purely shape based approaches for matching across viewpoint variation.

关键词： Graphic methods

来源：评论

学校读者我要写书评

暂无评论

Multi-modal abnormality detection in video with unknown data segmentation

Multi-modal abnormality detection in video with unknown data...

引用

21st International Conference on pattern recognition, ICPR 2012

作者： Nguyen, Tien Vu Phung, Dinh Rana, Santu Pham, Duc Son Venkatesh, Svetha Centre for Pattern Recognition and Data Analytics Deakin University VIC Australia Department of Computing Curtin University WA Australia

ISBN: (纸本)9784990644109

This paper examines a new problem in large scale stream data: abnormality detection which is localized to a data segmentation process. Unlike traditional abnormality detection methods which typically build one unified model across data stream, we propose that building multiple detection models focused on different coherent sections of the video stream would result in better detection performance. One key challenge is to segment the data into coherent sections as the number of segments is not known in advance and can vary greatly across cameras;and a principled way approach is required. To this end, we first employ the recently proposed infinite HMM and collapsed Gibbs inference to automatically infer data segmentation followed by constructing abnormality detection models which are localized to each segmentation. We demonstrate the superior performance of the proposed framework in a real-world surveillance camera data over 14 days. © 2012 ICPR Org Committee.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

A nonparametric Bayesian Poisson gamma model for count data

A nonparametric Bayesian Poisson gamma model for count data

引用

International Conference on pattern recognition

作者： Sunil Kumar Gupta Dinh Phung Svetha Venkatesh Centre for Pattern Recognition and Data Analytics Deakin University Australia

ISBN: (纸本)9781467322164

关键词： data models Analytical models Bayesian methods Dictionaries Face Load modeling Indexes

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10页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：