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

34 篇 会议
2 篇 期刊文献

馆藏范围

36 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

14 篇 工学
- 10 篇 计算机科学与技术...
- 8 篇 软件工程
- 4 篇 控制科学与工程
- 3 篇 机械工程
- 2 篇 信息与通信工程
- 1 篇 化学工程与技术
6 篇 管理学
- 4 篇 管理科学与工程(可...
- 2 篇 图书情报与档案管...
5 篇 理学
- 2 篇 数学
- 2 篇 物理学
- 1 篇 化学
- 1 篇 统计学（可授理学、...

主题

9 篇 visualization
8 篇 feature extracti...
7 篇 image color anal...
6 篇 data mining
6 篇 training
5 篇 semantics
4 篇 support vector m...
4 篇 humans
3 篇 image segmentati...
3 篇 image edge detec...
3 篇 computers
2 篇 conferences
2 篇 computational co...
2 篇 dictionaries
2 篇 videos
2 篇 educational inst...
2 篇 vectors
2 篇 optimization
2 篇 monitoring
2 篇 image retrieval

机构

8 篇 chinese academy ...
6 篇 chinese academy ...
6 篇 university of ch...
4 篇 key laboratory o...
4 篇 school of comput...
4 篇 college of compu...
3 篇 key laboratory o...
3 篇 key lab of intel...
3 篇 key lab of intel...
2 篇 university of sc...
2 篇 national laborat...
2 篇 university of th...
2 篇 key laboratory o...
2 篇 institute of inf...
2 篇 megvii inc
2 篇 institute of mic...
2 篇 school of comput...
2 篇 key lab. of inte...
2 篇 key laboratory o...
2 篇 peng cheng labor...

作者

15 篇 qingming huang
11 篇 shuqiang jiang
5 篇 huang qingming
4 篇 liang li
4 篇 weiqiang wang
3 篇 chunxi liu
3 篇 zhang chunjie
3 篇 wang weiqiang
3 篇 liang chao
3 篇 wang shuhui
3 篇 wen gao
2 篇 huiying liu
2 篇 tian qi
2 篇 zheng-jun zha
2 篇 xiaoping sun
2 篇 liu jing
2 篇 shuhui wang
2 篇 zhipeng wu
2 篇 li su
2 篇 junbiao pang

语言

35 篇 英文
1 篇 其他

检索条件"机构=Key Laboratory of Intell. Information Process. Institute of Computing Technology"

共 36 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：

Beyond bag of words: Image representation in sub-semantic space 13

Beyond bag of words: Image representation in sub-semantic sp...

引用

21st ACM International Conference on Multimedia, MM 2013

作者： Zhang, Chunjie Wang, Shuhui Liang, Chao Liu, Jing Huang, Qingming Li, Haojie Tian, Qi School of Computer and Control Engineering University of Chinese Academy of Sciences 100049 Beijing China Key Lab of Intell. Info. Process Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Computer National Engineering Research Center for Multimedia Software Wuhan University 430072 Wuhan China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China School of Software Dalian University of Technology Liaoning China Department of Computer Sciences University of Texas San Antonio TX 78249 United States

ISBN: (纸本)9781450324045

Due to the semantic gap, the low-level features are not able to semantically represent images well. Besides, traditional semantic related image representation may not be able to cope with large inter class variations and are not very ro- bust to noise. To solve these problems, in this paper, we propose a novel image representation method in the sub- semantic space. First, examplar classifiers are trained by separating each training image from the others and serve as the weak semantic similarity measurement. Then a graph is constructed by combining the visual similarity and weak se- mantic similarity of these training images. We partition this graph into visually and semantically similar sub-sets. Each sub-set of images are then used to train classifiers in order to separate this sub-set from the others. The learned sub-set classifiers are then used to construct a sub-semantic space based representation of images. This sub-semantic space is not only more semantically meaningful but also more reli- Able and resistant to noise. Finally, we make categorization of images using this sub-semantic space based representation on several public datasets to demonstrate the e®ectiveness of the proposed method. Copyright © 2013 ACM.

关键词： Image representation

来源：评论

学校读者我要写书评

暂无评论

Undo the codebook bias by linear transformation for visual applications 13

Undo the codebook bias by linear transformation for visual a...

引用

21st ACM International Conference on Multimedia, MM 2013

作者： Zhang, Chunjie Zhang, Yifan Wang, Shuhui Pang, Junbiao Liang, Chao Huang, Qingming Tian, Qi School of Computer and Control Engineering University of Chinese Academy of Sciences 100049 Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China Key Lab of Intell. Info. Process Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China College of Computer Science and Technology Beijing University of Technology 100124 Beijing China School of Computer National Engineering Research Center for Multimedia Software Wuhan University 430072 Wuhan China Department of Computer Sciences University of Texas at San Antonio San Antonio TX 78249 United States

ISBN: (纸本)9781450324045

The bag of visual words model (BoW) and its variants have demonstrate their effectiveness for visual applications and have been widely used by researchers. The BoW model first extracts local features and generates the corresponding codebook, the elements of a codebook are viewed as visual words. The local features within each image are then encoded to get the final histogram representation. However, the codebook is dataset dependent and has to be generated for each image dataset. This costs a lot of computational time and weakens the generalization power of the BoW model. To solve these problems, in this paper, we propose to undo the dataset bias by codebook linear transformation. To represent every points within the local feature space using Euclidean distance, the number of bases should be no less than the space dimensions. Hence, each codebook can be viewed as a linear transformation of these bases. In this way, we can transform the pre-learned codebooks for a new dataset. However, not all of the visual words are equally important for the new dataset, it would be more effective if we can make some selection using sparsity constraints and choose the most discriminative visual words for transformation. We propose an alternative optimization algorithm to jointly search for the optimal linear transformation matrixes and the encoding parameters. Image classification experimental results on several image datasets show the effectiveness of the proposed method. Copyright © 2013 ACM.

关键词： Linear transformations

来源：评论

学校读者我要写书评

暂无评论

Multiscale Browsing through Video Collections in Smartphones Using Scalable Storyboards

Multiscale Browsing through Video Collections in Smartphones...

引用

IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Luis Herranz Key Laboratory of Intell. Information Process. Institute of Computing Technology Chinese Academy of Sciences Beijing China

This paper explores how multiscale browsing can be integrated with smart phone interfaces to provide enhanced navigation through video collections. We propose a system that allows the user to interactively change the scale of the storyboards, so the user can easily adjust the amount of information provided by them. Three different methods to select key frames are studied, including an efficient method that analyzes the video and creates a scalable description, with very little computational cost. Then, storyboards of any length can be retrieved on demand without any further analysis, which is very convenient to provide fast multiscale navigation. Experimental evaluations show how this method improves the utility of the summaries and enhances user experience.

关键词： Smart phones Browsers Semantics Clustering algorithms Navigation Algorithm design and analysis Computers

来源：评论

学校读者我要写书评

暂无评论

Theoretical analysis of learning local anchors for classification

Theoretical analysis of learning local anchors for classific...

引用

International Conference on Pattern Recognition

作者： Junbiao Pang Qingming Huang Baocai Yin Lei Qin Dan Wang College of Computer Science and Technology Beijing University of Technology China Key Laboratory of Intell. Information Process. Institute of Comput. Technology Chinese Academy of Sciences China

ISBN: (纸本)9781467322164

In this paper, we present a theoretical analysis on learning anchors for local coordinate coding (LCC), which is a method to model functions for data lying on non-linear manifolds. In our analysis several local coding schemes, i.e., orthogonal coordinate coding (OC-C), local Gaussian coding (LGC), local Student coding (LSC), are theoretically compared, in terms of the upper-bound locality error on any high-dimension data; this provides some insight to understand the local coding for classification tasks. We further give some interesting implications of our results, such as tradeoff between locality and approximation ability in learning anchors.

关键词： Encoding Upper bound Approximation methods Manifolds Educational institutions Vectors Error analysis

来源：评论

学校读者我要写书评

暂无评论

A simple and effective saliency detection approach

A simple and effective saliency detection approach

引用

International Conference on Pattern Recognition

作者： Hui Zhang Weiqiang Wang Guiping Su Lijuan Duan Chinese Academy of Sciences Beijing China Key Laboratory of Intell. Information Process. Institute of Computing Technology CAS Beijing China College of Computer Science and Technology Beijing University of Technology Beijing China

This paper presents a simple and effective method to compute the pixel saliency with full resolution in an image. First, the proposed method creates an image representation of four color channels through the modified computation on the basis of Itti et al.[5]. Then the most informative channel is automatically identified from the derived four color channels. Finally, the pixel saliency is computed through the simple combination of contrast feature and spatial attention function on the individual channel. The proposed method is computationally very simple, but it achieves a very good performance in the comparison experiments with six other saliency detection methods. On the challenging database with 1,000 images, it outperforms six other methods in both identifying salient pixels and segmenting salient regions.

关键词： Image color analysis Visualization Humans Image segmentation Databases Biological system modeling

来源：评论

学校读者我要写书评

暂无评论

Effectively localize text in natural scene images

Effectively localize text in natural scene images

引用

International Conference on Pattern Recognition

作者： Xiaoqian Liu Ke Lu Weiqiang Wang Chinese Academy of Sciences Beijing China Key Laboratory of Intell. Information Process. Institute of Comput. Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781467322164

In this paper, we present an effective approach to locate scene text in images based on connected components analysis (CCA). Our approach first utilizes a multi-scale adaptive local thresholding operator to convert an image into two complementary binary images. Then, connected components (CCs) are extracted from both of them, which ensures that bright or dark text in contrast to background can be detected. Further, some rules are designed based on stroke features to verify whether a connected component belongs to characters, and the obtained candidate components are further checked on the word level by using a graph to represent spatial relation of different components. Finally, scene text regions are localized by searching the collinear maximum group over the graph. The comparison experiments of the proposed method with some representative state-of-the-art methods, on the challenging dataset ICDAR 2003, show that the proposed approach is very effective, and it is robust to text of different sizes, fonts, colors, as well as orientation of text lines.

关键词： Feature extraction Image color analysis Image edge detection Robustness Videos Learning systems Training

来源：评论

学校读者我要写书评

暂无评论

Color Maximal-Dissimilarity Pattern for pedestrian detection

Color Maximal-Dissimilarity Pattern for pedestrian detection

引用

International Conference on Pattern Recognition

作者： Qingyuan Wang Junbiao Pang Guoyi Liu Lei Qin Qingming Huang Shuqiang Jiang Chinese Academy of Sciences China College of Computer Science and Technology Beijing University of Technology China NEC Laboratories China Beijing China Key Laboratory of Intell. Information Process. Institute of Comput. Technology CAS China

ISBN: (纸本)9781467322164

Feature plays an important role in pedestrian detection, and considerable progress has been made on shape-based descriptors. However, color cues have barely been devoted to detection tasks, seemingly due to the variable appearance of pedestrians. In this paper, Color Maximal-Dissimilarity Pattern (CMDP) is proposed to encode color cues by two core operations, i.e., oriented filtering and max-pooling, which emulate the functions of primary visual cortex (V1). The extensively experimental results reveal that the biologically-explainable encoding scheme increases the invariance of color cues, and outperforms the state-of-the-art color descriptor in terms of both accuracy and speed.

关键词： Image color analysis Cascading style sheets Histograms Feature extraction Visualization Shape Biology

来源：评论

学校读者我要写书评

暂无评论

Multi-feature metric learning with knowledge transfer among semantics and social tagging

Multi-feature metric learning with knowledge transfer among ...

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Shuhui Wang Shuqiang Jiang Qingming Huang Qi Tian Key Laboratory of Intell. Information Process.(CAS) Institute of Comput. Technology CAS Beijing China Chinese Academy of Sciences Beijing China Department of Computer Science University of Texas at San Antonio TX USA

Previous metric learning approaches learn a unified metric for all the classes on single feature representation, thus cannot be directly transplanted to applications involving multiple features, hundreds to thousands of hierarchical structured semantics and abundant social tagging. In this paper, we propose a novel multi-task multi-feature metric learning method which models the information sharing mechanism among different learning tasks. We decompose the real world multi-class problems such as semantic categorization or automatic tagging into a set of tasks where each task corresponds to several classes with strong visual correlation. We conduct metric learning to learn a set of (hyper)category-specific metrics for all the tasks. By encouraging model sharing among tasks, more generalization power is acquired. Another advantage is the capability of simultaneous learning with semantic information and social tagging based on the multi-task learning framework, and thus they both benefit from the information provided by each other. Experiments demonstrate the advantages on applications including semantic categorization and automatic tagging compared with other popular metric learning approaches.

关键词： Measurement Kernel Semantics Tagging Training Visualization Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Fast and effectively identify pornographic images

Fast and effectively identify pornographic images

引用

2011 7th International Conference on Computational intell.gence and Security, CIS 2011

作者： Fu, Yanjun Wang, Weiqiang School of Information Science and Engineering Graduate University of Chinese Academy of Sciences Beijing China Key Lab. of Intell. Info. Process. Institute of Computing Technology CAS Beijing China

ISBN: (纸本)9780769545844

In this paper, we present a practical solution to identifying pornographic images based on multiple low-level image features and support vector machine (SVM). First, the region of interest (ROI) is obtained from an original image based on the detection of skin-like pixels in YCbCr color space. The ROI is then classified into being acceptable or unacceptable by its size. Images without ROIs or acceptable ROIs are deemed to be benign images. For images with acceptable ROI, the color, texture and shape features are further extracted on ROI, and then fed to a SVM classifier to perform the task of recognition. Our approach has obtained 96.05% sensitivity and 96.17% specificity on a dataset containing 8,000 pornographic images and 12,500 benign images, as well as the process.ng speed of about 0.026 seconds for a PC to determine whether a given image with an average size of 420 by 433 pixels is pornographic. © 2011 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Fast and Effectively Identify Pornographic Images

Fast and Effectively Identify Pornographic Images

引用

International Conference on Computational intell.gence and Security

作者： Yanjun Fu Weiqiang Wang School of Information Science and Engineering Chinese Academy of Sciences Beijing China Key Laboratory of Intell. Information Process. Institute of Computing Technology CAS Beijing China

ISBN: (纸本)9781457720086

关键词： Feature extraction Image color analysis Skin Support vector machines Shape Vectors Image 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4页 << < 1 2 3 4 > >>

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：