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

40 篇 会议
5 篇 期刊文献

馆藏范围

45 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

28 篇 工学
- 20 篇 计算机科学与技术...
- 16 篇 软件工程
- 7 篇 信息与通信工程
- 6 篇 控制科学与工程
- 2 篇 机械工程
- 2 篇 建筑学
- 2 篇 环境科学与工程（可...
- 1 篇 光学工程
- 1 篇 仪器科学与技术
- 1 篇 动力工程及工程热...
- 1 篇 电气工程
- 1 篇 土木工程
- 1 篇 测绘科学与技术
- 1 篇 化学工程与技术
- 1 篇 农业工程
- 1 篇 生物工程
14 篇 理学
- 12 篇 数学
- 3 篇 物理学
- 2 篇 统计学（可授理学、...
- 1 篇 化学
- 1 篇 生物学
- 1 篇 生态学
9 篇 管理学
- 7 篇 图书情报与档案管...
- 2 篇 管理科学与工程(可...
- 1 篇 工商管理
2 篇 农学
- 1 篇 作物学
- 1 篇 农业资源与环境
1 篇 经济学
- 1 篇 应用经济学
1 篇 法学
- 1 篇 社会学
1 篇 军事学

主题

9 篇 machine intellig...
8 篇 pattern analysis
5 篇 system analysis ...
4 篇 design engineeri...
3 篇 image segmentati...
3 篇 neural networks
3 篇 data mining
3 篇 pattern recognit...
3 篇 genetic algorith...
3 篇 classification (...
2 篇 learning systems
2 篇 image matching
2 篇 support vector m...
2 篇 computer archite...
2 篇 systems engineer...
2 篇 voting
2 篇 image edge detec...
2 篇 computational in...
2 篇 intelligent robo...
2 篇 convergence

机构

3 篇 pattern analysis...
2 篇 pattern analysis...
2 篇 department of co...
2 篇 pattern analysis...
2 篇 pattern analysis...
2 篇 pattern analysis...
2 篇 pattern analysis...
1 篇 university of sc...
1 篇 pattern analysis...
1 篇 visual artificia...
1 篇 universitat autò...
1 篇 cibm center for ...
1 篇 real-time embedd...
1 篇 faculty of engin...
1 篇 miit key laborat...
1 篇 university of ab...
1 篇 xlab d.o.o. ljub...
1 篇 university of ch...
1 篇 department of nu...
1 篇 radiology depart...

作者

10 篇 kamel mohamed s.
8 篇 kamel mohamed
4 篇 m. kamel
3 篇 m.s. kamel
2 篇 f. karray
2 篇 kong adams
2 篇 bakus jan
2 篇 alhichri haikel ...
2 篇 h.r. tizhoosh
2 篇 wanas nayer m.
2 篇 y. yang
2 篇 makrehchi masoud
2 篇 mohamed s. kamel
2 篇 you jane
2 篇 zhang david
2 篇 karray fakhri
2 篇 sun yanmin
2 篇 cheung king-hong
1 篇 ghojogh benyamin
1 篇 li xi

语言

45 篇 英文

检索条件"机构=Pattern Analysis and Machine Intelligence Lab"

共 45 条记录，以下是11-20 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：

Particle swarm clustering ensemble 08

Particle swarm clustering ensemble

引用

10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008

作者： Ahmadi, Abbas Karray, Fakhri Kamel, Mohamed Pattern Analysis and Machine Intelligence Lab. Department of Systems Design Engineering University of Waterloo 200 University Avenue West Waterloo ON Canada

ISBN: (纸本)9781605581309

Extracting natural groups of the unlabeled data is known as clustering. To improve the stability and robustness of the clustering outputs, clustering ensembles have emerged recently. In this paper, an ensemble of particle swarm clustering algorithms is proposed. That is, the members of the ensemble are based on the cooperative swarms clustering approaches. The performance of the proposed particle swarm clustering ensemble is evaluated using different data sets and is compared to that of other clustering techniques.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

Learning term dependency links using information theoretic inclusion measure

Learning term dependency links using information theoretic i...

引用

17th IEEE International Conference on Data Mining Workshops, ICDM Workshops 2007

作者： Makrehchi, Masoud Kamel, Mohamed S. Pattern Analysis and Machine Intelligence Lab. Department of Electrical and Computer Engineering University of Waterloo Waterloo ON N2L 3G1 Canada

ISBN: (纸本)0769530192

An algorithm to identify and remove term redundancy is proposed for text classifiers using ranking-based feature selection. The proposed method employs a normalized mutual information, which is called inclusion measure, to estimate asymmetric dependency between two terms. Based on pair-wise dependency measures, a dependency matrix is constructed. In this paper, an algorithm is proposed to learn term dependency links from term dependency matrix, and visualize the dependency between term in a graph called term dependency tree. All nodes of the tree are categorized into two groups: hubs and links. Any node whose outdegree is less than two will join the Links group. We show that all link nodes are most likely redundant. We also introduce a criterion, which is called substitution cost, to decide whether to remove or retain a candidate, redundant term. The proposed approach is applied to four well-known benchmark data sets with a SVM and Rocchio classifier using a set of highly aggressive feature selection schemes. The results show the effectiveness of the proposed method especially when applied to weak classifiers. © 2007 IEEE.

关键词： Forestry

来源：评论

学校读者我要写书评

暂无评论

Combining feature ranking for text classification

Combining feature ranking for text classification

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Masoud Makrehchi Mohamed S. Kamel Pattern Analysis and Machine Intelligence Lab Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada

Feature ranking is one of the dimensionality reduction methods. Because of its simplicity and low cost, it is widely used in text classification. One problem with feature ranking methods is their non-robust behavior when applied to different data sets. In other words, the feature ranking methods behave differently from one data set to the other. The problem is more complex when we consider that the performance of feature ranking methods is different when being used by different classifiers. In this paper, a new method based on combining feature rankings is proposed to find the best features among a set of feature rankings. Four preferential voting method are employed to combine feature rankings obtained by eight well-known ranking measures. According to the results, combining methods can offer reliable results that are very close to the best solution without the need to use a classifier. The proposed method is applied to the text classification problem and evaluated on three well-known data sets using SVM classifier.

关键词： Text categorization Support vector machines Support vector machine classification Voting Training data Particle measurements Niobium compounds pattern analysis machine intelligence Costs

来源：评论

学校读者我要写书评

暂无评论

Fuzzy reinforcement learning for embedded soccer agents in a multi-agent context

Fuzzy reinforcement learning for embedded soccer agents in a...

引用

作者： Tehrani, A.M. Kamel, M.S. Khamis, A.M. Pattern Analysis and Machine Intelligence Lab. Electrical and Computer Engineering Department University of Waterloo Waterloo Ont. N2L 3G1 Canada Mechanical Engineering Department University of Waterloo Canada Department of Cooperative Intelligent Systems Canada Pattern Analysis and Machine Intelligence Laboratory University of Waterloo Canada Department of Systems Engineering and Automation Carlos III University of Madrid Spain

The work presented in this paper aims at combining fuzzy function approximation and reinforcement learning in order to create robotic soccer agents that are able to coordinate their behaviours locally and socially while learning from experience. This simultaneous coordination and learning ability can play a crucial role in improving the behaviour usage of robotic soccer agents. To achieve this goal, a fuzzy reinforcement learning technique for a single agent is first examined and then this technique is applied to multiple agents. The conducted experiments through a soccer simulation system show that the performance of robot scoring speed is improved using the proposed approach.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Enhancing Temporal Classification of AAR Parameters in EEG single-trial analysis for Brain-Computer Interfacing

Enhancing Temporal Classification of AAR Parameters in EEG s...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： G.S. Dharwarkar O. Basir Pattern Analysis and Machine Intelligence PAMI Lab Electrical and Computer Engineering University of Waterloo Canada

Adaptive autoregressive (AAR) coefficients provide dynamic spectral information in EEG single-trial analysis. In this paper we propose a temporal evidence accumulation framework to enhance classification of AAR features. The results for a single subject, using 280 trials, indicate distinct improvements over a conventional method of temporal classification. We illustrate how the framework is applicable to AAR features, as well as to wavelet features as reported in Lemm et al., (2004). These findings put the two time-frequency features on equal footing for comparison in this context

关键词： Electroencephalography Brain modeling Protocols Biomedical engineering Synchronous motors pattern analysis Context modeling Predictive models Data analysis Signal analysis

来源：评论

学校读者我要写书评

暂无评论

Revealing the secret of FaceHashing

引用

International Conference on Biometrics, ICB 2006

作者： Cheung, King-Hong Kong, Adams Zhang, David Kamel, Mohamed You, Jane Biometrics Research Centre Department of Computing Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong Pattern Analysis and Machine Intelligence Lab. University of Waterloo 200 University Avenue West Ont. Canada

ISBN: (纸本)3540311114

Biometric authentication has attracted substantial attention over the past few years. It has been reported recently that a new technique called FaceHashing, which is proposed for personal authentication using face images, has achieved perfect accuracy and zero equal error rates (EER). In this paper, we are going to reveal that the secret of FaceHashing in achieving zero EER is based on a false assumption. This is done through simulating the claimants' experiments. Thus, we would like to alert the use of "safe" token. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

ART-based Clustering Aggregation

ART-based Clustering Aggregation

引用

IEEE International Conference on Granular Computing (GRC)

作者： Y. Yang M.S. Kamel F. Jin School of Information Science and Technology Southwest Jiaotong University Chengdu China Pattern Analysis and Machine Intelligence Lab the Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada

来源：评论

学校读者我要写书评

暂无评论

A Distributed Architecture for Mobile Multirobot Remote Interaction

A Distributed Architecture for Mobile Multirobot Remote Inte...

引用

IEEE Workshop on Distributed Intelligent Systems: Collective intelligence and Its Applications (DIS)

作者： A. Khamis A. Abdel-Rahrnan M. Kamel RoboticsLaboratory Department of Systems Engineering and Automation Carlos III Technical University of Madrid Madrid Spain RoboticsLab Carlos III University of Madrid Leganes Madrid Spain Pattern Analysis and Machine Intelligence (PAMI) Lab University of Waterloo Canada West Waterloo Ontario Canada

This paper presents a distributed architecture based on the usage of intelligent user interfaces and multiagent systems to facilitate cooperative Internet-based remote interaction with a multirobot system. The proposed system relies on the agent paradigm for dealing with the size and complexity of cooperative remote interaction systems with multirobots, while taking advantage of intelligent user interfaces for obtaining high degree of naturalness during the interaction sessions. This generic architecture, featuring multimodality and adaptivity, supports an unlimited number of robots, an unlimited number of behaviors, and offers different operation modes making it a suitable platform for mobile multirobot remote interaction. Two different application scenarios based on this architecture are implemented and demonstrated to verify the architecture's efficacy

关键词： Robot kinematics Intelligent robots Human robot interaction Computer architecture Multirobot systems Internet Intelligent agent Robotics and automation machine intelligence Mobile robots

来源：评论

学校读者我要写书评

暂无评论

Parameter inference of cost-sensitive boosting algorithms

引用

4th International Conference on machine Learning and Data Mining in pattern Recognition, MLDM 2005

作者： Sun, Yanmin Wong, A.K.C. Wang, Yang Pattern Analysis and Machine Intelligence Lab. University of Waterloo Canada Pattern Discovery Software Ltd.

ISBN: (纸本)3540269231

Several cost-sensitive boosting algorithms have been reported as effective methods in dealing with class imbalance problem. Misclassification costs, which reflect the different level of class identification importance, are integrated into the weight update formula of AdaBoost algorithm. Yet, it has been shown that the weight update parameter of AdaBoost is induced so as the training error can be reduced most rapidly. This is the most crucial step of AdaBoost in converting a weak learning algorithm into a strong one. However, most reported cost-sensitive boosting algorithms ignore such a property. In this paper, we come up with three versions of cost-sensitive AdaBoost algorithms where the parameters for sample weight updating are induced. Then, their identification abilities on the small classes are tested on four "real world" medical data sets taken from UCI machine Learning Database based on F-measure. Our experimental results show that one of our proposed costsensitive AdaBoost algorithms is superior in achieving the best identification ability on the small class among all reported cost-sensitive boosting algorithms. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Algorithms

来源：评论

学校读者我要写书评

暂无评论

Design of multiple classifier systems for time series data

Design of multiple classifier systems for time series data

引用

6th International Workshop on Multiple Classifier Systems, MCS 2005

作者： Chen, Lei Kamel, Mohamed S. Pattern Analysis and Machine Intelligence Lab Electrical and Computer Engineering University of Waterloo Ont. N2L 3G1 Canada

In previous work, we showed that the use of Multiple Input Representation(MIR) for the classification of time series data provides complementary information that leads to better accuracy. [4]. In this paper, we introduce the Static Minimization-Maximization approach to build Multiple Classifier Systems(MCSs) using MIR. SMM consists of two steps. In the minimization step, a greedy algorithm is employed to iteratively select the classifiers from the knowledge space to minimize the training error of MCSs. In the maximization step, a modified version of Behavior Knowledge Space(BKS), Balanced Behavior Knowledge Space(BBKS), is used to maximize the expected accuracy of the whole system given that the training error is minimized. Several popular techniques including AdaBoost, Bagging and Random Subspace are used as the benchmark to evaluate the proposed approach on four time series data sets. The results obtained from our experiments show that the performance of the proposed approach is effective as well as robust for the classification of time series data. In addition, this approach could be further extended to other applications in our future research. © Springer-Verlag Berlin Heidelberg 2005.

关键词： pattern recognition

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5页 << < 1 2 3 4 5 > >>

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：