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

951 篇 会议
611 篇 期刊文献
2 册 图书

馆藏范围

1,564 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

957 篇 工学
- 630 篇 计算机科学与技术...
- 556 篇 软件工程
- 185 篇 信息与通信工程
- 181 篇 控制科学与工程
- 155 篇 生物工程
- 141 篇 生物医学工程（可授...
- 128 篇 光学工程
- 106 篇 机械工程
- 100 篇 电气工程
- 89 篇 电子科学与技术（可...
- 68 篇 化学工程与技术
- 57 篇 仪器科学与技术
- 36 篇 交通运输工程
- 34 篇 建筑学
- 31 篇 材料科学与工程（可...
- 31 篇 土木工程
- 27 篇 动力工程及工程热...
- 25 篇 力学（可授工学、理...
557 篇 理学
- 244 篇 数学
- 206 篇 物理学
- 167 篇 生物学
- 83 篇 统计学（可授理学、...
- 69 篇 化学
- 46 篇 系统科学
218 篇 管理学
- 115 篇 图书情报与档案管...
- 106 篇 管理科学与工程(可...
- 21 篇 工商管理
116 篇 医学
- 104 篇 临床医学
- 73 篇 基础医学(可授医学...
- 57 篇 药学(可授医学、理...
21 篇 法学
11 篇 经济学
11 篇 农学
9 篇 教育学
3 篇 文学
2 篇 军事学

主题

92 篇 feature extracti...
62 篇 training
49 篇 semantics
41 篇 task analysis
33 篇 deep learning
33 篇 accuracy
32 篇 electroencephalo...
32 篇 computational mo...
26 篇 object detection
26 篇 semantic segment...
26 篇 visualization
24 篇 cameras
24 篇 robustness
23 篇 neural networks
23 篇 predictive model...
22 篇 conferences
22 篇 generative adver...
21 篇 support vector m...
20 篇 machine learning
20 篇 data models

机构

240 篇 key laboratory o...
194 篇 school of comput...
81 篇 shenzhen college...
79 篇 school of data a...
76 篇 university of ch...
74 篇 college of intel...
69 篇 cas key laborato...
64 篇 peng cheng labor...
59 篇 guangdong provin...
53 篇 tianjin key labo...
44 篇 cas key laborato...
42 篇 tianjin key labo...
35 篇 guangdong-hong k...
32 篇 tianjin key labo...
31 篇 cas key laborato...
31 篇 guangdong provin...
29 篇 shenzhen institu...
27 篇 key laboratory o...
27 篇 anhui province k...
27 篇 the chinese univ...

作者

121 篇 zheng wei-shi
80 篇 guanglin li
58 篇 wu xinyu
44 篇 wei-shi zheng
42 篇 li guanglin
39 篇 yunong zhang
36 篇 xinyu wu
35 篇 xie xiaohua
28 篇 lai jianhuang
28 篇 shixiong chen
27 篇 fuji ren
25 篇 lai jian-huang
24 篇 mei yu
24 篇 peng fang
23 篇 wang xin
22 篇 oluwarotimi will...
22 篇 lu bao-liang
22 篇 ren fuji
21 篇 dang jianwu
20 篇 wang longbiao

语言

1,482 篇 英文
73 篇 其他
10 篇 中文

检索条件"机构=Key Laboratory of Machine Intelligence and Advanced Computing"

共 1564 条记录，以下是1481-1490 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：

Learning hierarchical translation spans

Learning hierarchical translation spans

引用

2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014

作者： Zhang, Jingyi Utiyama, Masao Sumita, Eiichro Zhao, Hai Department of Computer Science and Engineering Center for Brain-Like Computing and Machine Intelligence Shanghai Jiao Tong Unviersity Shanghai200240 China Key Laboratory Shanghai Education Commission Intelligent Interaction Cognitive Engineering Shanghai Jiao Tong Unviersity Shanghai200240 China National Institute of Information and Communications Technology 3-5Hikaridai Keihanna Science City Kyoto619-0289 Japan

ISBN: (纸本)9781937284961

We propose a simple and effective approach to learn translation spans for the hierarchical phrase-based translation model. Our model evaluates if a source span should be covered by translation rules during decoding, which is integrated into the translation system as soft constraints. Compared to syntactic constraints, our model is directly acquired from an aligned parallel corpus and does not require parsers. Rich source side contextual features and advanced machine learning methods were utilized for this learning task. The proposed approach was evaluated on NTCIR-9 Chinese-English and Japanese-English translation tasks and showed significant improvement over the baseline system. © 2014 Association for Computational Linguistics.

关键词： Syntactics

来源：评论

学校读者我要写书评

暂无评论

Dynamic facial expression recognition based on K-order emotional intensity model

Dynamic facial expression recognition based on K-order emoti...

引用

IEEE International Conference on Robotics and Biomimetics

作者： Changqin Quan Yao Qian Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China P.R. The Japan Federation of Engineering Societies University of Tokushima Shinkura-cho Tokushima Japan

ISBN: (纸本)9781479973989

With the development of artificial intelligence and pattern recognition, facial expression recognition plays a more and more important role in intelligent human-computer interaction. In this paper, we present a model named K-order emotional intensity model (K-EIM) which is based on K-Means clustering. Different from other related works, the proposed approach can quantify emotional intensity in an unsupervised way. And then the output from K-EIM is encoded. The coding results are used for the dynamic facial expression recognition. The experiment is conducted on Cohn-Kanade facial expression database and the support vector machine classifier is used for facial expression classification. This method achieved a dynamic facial expression recognition accuracy of 88.32% which suggest that the proposed method shows better performance and proves its validity. Moreover, effect of different segments of emotional intensity is also discussed in the paper.

关键词： Face recognition Encoding Accuracy Emotion recognition Principal component analysis Training Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Expression image preprocessing based on wavelet transform

Expression image preprocessing based on wavelet transform

引用

IEEE International Conference on Robotics and Biomimetics

作者： Changqin Quan Xiaoming Xu Fuji Ren The Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China P.R Hefei University of Technology Hefei Anhui CN The University of Tokushima Tokushima Japan

ISBN: (纸本)9781479973989

In this paper, we present a new image preprocessing method which is based on Wavelet Transform. Before we extract expression texture information, Wavelet transform will be applied to remove partial high frequency information. And then Gabor Transform will be used to extract expression information. At last we chose the Support Vector machine to classify facial expressions. Experiments on the Japanese Female Facial Expression (JAFFE) Database illustrate that the Wavelet Transform and Gabor features are effective for facial expression discrimination. Additionally, the experiment results validate the feasibility of this method.

关键词： Decision support systems Conferences Robots Biomimetics XML Wavelet transforms

来源：评论

学校读者我要写书评

暂无评论

MODELING BLOG USER FOR CHINESE MICRO-BLOG SENTIMENT CLASSIFICATION WITH FUZZY SVM

MODELING BLOG USER FOR CHINESE MICRO-BLOG SENTIMENT CLASSIFI...

引用

2014 IEEE 3rd International Conference on Cloud computing and intelligence Systems

作者： Xiao Sun Chengcheng Li Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and InformationHefei University of Technology Faculty of Engineering University of Tokushima2-1 Minami-JosanjimaTokushima 770-8506Japan

ISBN: (纸本)9781467369541

Micro-blog is easily posted and communicated because of its short text ***,its brevity limits the feature *** paper presents a blogger modeling method for Chinese micro-blog sentiment *** paper would adopt a multidimensional strategy to accomplish the feature extraction *** with traditional feature extraction methods and combined with the interactive property of blog,the blog comment will be considered as the performance characteristic of micro-blog emotion *** comes to comments content and the relationship between commentators and micro-bloggers while it extracts the micro blogging text *** last,the paper adopts fuzzy SVM model to reduce the sensation of noise points and outliers on classification *** results demonstrate the effectiveness of the multidimensional feature extraction method on sentiment classification and the classify effect of fuzzy SVM is better than SVM.

关键词： sentiment classification multidimensional fuzzy SVM

来源：评论

学校读者我要写书评

暂无评论

NEW WORD DETECTION AND EMOTIONAL TENDENCY JUDGMENT BASED ON MIXED MODEL

NEW WORD DETECTION AND EMOTIONAL TENDENCY JUDGMENT BASED ON ...

引用

2014 IEEE 3rd International Conference on Cloud computing and intelligence Systems

作者： Xiao Sun Chongyuan Sun Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and InformationHefei University of Technology Faculty of Engineering University of Tokushima2-1 Minami-JosanjimaTokushima 770-8506Japan

ISBN: (纸本)9781467369541

The paper studies a new method for Chinese new word detection and emotional tendency judgment based on mixed model and proposes a new word generation *** we construct conditional random fields(CRFs) to recognize the new words,lead-in features based on character combined with the crowd sourcing network *** then express word as a word vector based on neural network language model(NNLM) to judge the new word emotional *** experimental results show that the method can improve the precision and recall of the new word detection with a good system performance,and it also provides a new way for forecasting the public mood.

关键词： New Word Detection Conditional Random Fields Emotional Tendency Judgment Neural Network Language Model

来源：评论

学校读者我要写书评

暂无评论

MINING THE IMPACT OF SOCIAL NEWS ON THE EMOTIONS OF USERS BASED ON DEEP MODEL

MINING THE IMPACT OF SOCIAL NEWS ON THE EMOTIONS OF USERS BA...

引用

2014 IEEE 3rd International Conference on Cloud computing and intelligence Systems

作者： Xiao Sun Fei Gao Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and InformationHefei University of Technology Faculty of Engineering University of Tokushima2-1 Minami-JosanjimaTokushima 770-8506Japan

ISBN: (纸本)9781467369541

In this paper,Deep Belief Nets(DBN) model and Support Vector machine(SVM) are used to mine the features hidden in social news,which can influence the emotions of *** feature selection methods for text modeling are used to build the input vectors of DBN,with the purpose of keeping the text information to the greatest *** take advantage of the deep features abstracted by DBN to build social news text *** the same time,three optimal models are used as inputs of SVM to train and classify the social *** get a conclusion that DBN not only reduces the dimension of original features,but also makes the abstracted features with more text information and shows better performance in determining the influence on people' s emotions by social news.

关键词： Deep Belief Network(DBN) Restricted Boltzmann machine(RBM) Impacts on Emotion Social News

来源：评论

学校读者我要写书评

暂无评论

A Connected Component-Based Distributed method for overlapping community detection

A Connected Component-Based Distributed method for overlappi...

引用

International Conference on computing and Networking Technology (ICCNT)

作者： Tian Chen Kai Liu Xin Yi Dandan Shen Wei Wang Fuji Ren Jun Liu Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei AnHui Agricultural University Hefei School of Computer and Information Hefei University of Technology Hefei The University of Tokushima Japan

ISBN: (纸本)9781479926978

In order to find the overlapping community structure more quickly and accurately in complex network, this paper proposes a Connected Component-Based Distributed method (CCBD) for overlapping community detection. CCBD first divides edges set in the network into smaller one. Next, it seeks out connected component using distributed platforms and gives a serials number to them according to certain rules. Then, it classifies these connected components according to the serials number. Task nodes determine whether any two connected components and non-propagating edges can be connected to become a larger community. Finally, CCBD negotiates a new serials name for the new community. Through repeated iterations, we get the community structure in the network. Nodes belong to multiple communities are overlapping nodes. Experiment results show that CCBD has higher time efficiency benefiting from distributed computing. Moreover, the quality of communities detected by CCBD surpasses those found by other algorithms.

关键词： Communities Algorithm design and analysis Educational institutions Complex networks Clustering algorithms Distributed computing Complexity theory

来源：评论

学校读者我要写书评

暂无评论

Chinese Microblog Sentiment Classification Based on Deep Belief Nets with Extended Multi-Modality Features

Chinese Microblog Sentiment Classification Based on Deep Bel...

引用

IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Xiao Sun Chengcheng Li Wanyi Xu Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China School of Information Science and Engineering Southeast University Shanghai China Faculty of Engineering University of Tokushima Tokushima Japan

ISBN: (纸本)9781479942732

This paper presents a DBN (deep belief nets) model and a multi-modality feature extraction method to extend features' dimensionalities of short text for Chinese micro blogging sentiment classification. Besides traditional features sets for document classification, comments for certain posts are also extracted as part of the micro blogging features according to the relationship between commenters and posters though constructing micro blogging social network as input information. Then, the integration of the above modality features is combined and represented as input vector for DBN. In this paper, a DBN model, which is stacked with several layers of RBM (Restricted Boltzmann machine), is implemented to initialize the structure of neural network. The RBM layers can take probability distribution samples of original data to learn hidden structures for better feature representation. A Class RBM (Classification RBM) layer, which is stacked on top of several RBM layers, is adapted to achieve the final sentiment classification. The results demonstrate that, with proper structure and parameter, the performance of the proposed deep learning method on sentiment classification is better than state of the art surface learning models such as SVM or NB, which proves that DBN is suitable for short-length document classification with the proposed feature dimensionality extension method.

关键词： Feature extraction Semantics Visualization Training Social network services Blogs Educational institutions

来源：评论

学校读者我要写书评

暂无评论

Extracting three-dimensional Cellular Automaton for cement microstructure development using Gene Expression Programming

Extracting three-dimensional Cellular Automaton for cement m...

引用

World Congress on Nature & Biologically Inspired computing (NaBIC)

作者： Zhifeng Liang Bo Yang Lin Wang Xiaoqian Zhang Nana He Ajith Abraham Shandong Provincial Key Laboratory of Network based Intelligent Computing University of Jinan Jinan China IT4Innovations VSB-Technical University of Ostrava Ostrava Czech Republic Machine Intelligence Research Labs (MIR Labs) WA USA

A three-dimensional CA model for the simulation of Portland cement microstructure development has been developed in this paper. The Gene Expression Programming (GEP) algorithm is employed as the learning algorithm to evolve the transition rule reversely from the microstructure development characteristic data due to hydration reactions. The characteristic data is extracted from 8-bit gray images that based on the processing of real cement acquired by Micro Computed Tomography (micro-CT) technology. Starting with initial micro-CT image, cement microstructure evolution images of 28 days is constructed through CA rule discovered by GEP. The experimental results show that this model with the CA rule designed by GEP has higher agreement between the model predictions and experimental measurements for degree of hydration than other models. Furthermore, this model still has good generalization ability when changing the water-cement ratio and chemical composition.

关键词： Computational modeling Predictive models Mathematical model Programming Prediction algorithms TV Equations

来源：评论

学校读者我要写书评

暂无评论

Improvement of FCM neural network classifier using K-Medoids clustering

Improvement of FCM neural network classifier using K-Medoids...

引用

World Congress on Nature & Biologically Inspired computing (NaBIC)

作者： Xiaoqian Zhang Bo Yang Lin Wang Zhifeng Liang Ajith Abraham Shandong Provincial Key Laboratory of Network based Intelligent Computing University of Jinan Jinan China IT4Innovations VSB-Technical University of Ostrava Ostrava Czech Republic Machine Intelligence Research Labs (MIR Labs) WA USA

Floating Centroids Method (FCM) is a new method to improve the performance of neural network classifier. But the K-Means clustering algorithm used in FCM is sensitive to outliers. So this weakness will influence the performance of classifier to a certain extent. In this paper, K-Medoids clustering algorithm which can diminish the sensitivity to the outliers is used to partition the mapping points into some disjoint subsets to improve FCM's robustness and performance. Some data sets from UCI machine Learning Repository are employed in our experiments. The results show a better performance for the FCM using our improved method.

关键词： Iris Vehicles Sensitivity Robustness Clustering algorithms Color

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157页 << < 145 146 147 148 149 150 151 152 153 154 > >>

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：