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

654 篇 会议
2 册 图书

馆藏范围

656 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

648 篇 工学
- 406 篇 机械工程
- 298 篇 计算机科学与技术...
- 17 篇 电气工程
- 14 篇 软件工程
- 11 篇 光学工程
- 4 篇 信息与通信工程
- 2 篇 控制科学与工程
- 2 篇 生物医学工程（可授...
- 2 篇 生物工程
- 1 篇 仪器科学与技术
- 1 篇 电子科学与技术（可...
- 1 篇 土木工程
- 1 篇 化学工程与技术
14 篇 理学
- 11 篇 物理学
- 5 篇 数学
- 3 篇 生物学
- 2 篇 系统科学
- 2 篇 统计学（可授理学、...
- 1 篇 化学
5 篇 管理学
- 3 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
1 篇 法学
- 1 篇 社会学
1 篇 教育学
- 1 篇 教育学
1 篇 医学
- 1 篇 基础医学(可授医学...
- 1 篇 临床医学
- 1 篇 药学(可授医学、理...

主题

251 篇 computer vision
94 篇 image segmentati...
90 篇 cameras
86 篇 layout
84 篇 feature extracti...
83 篇 face recognition
82 篇 object recogniti...
76 篇 object detection
74 篇 image recognitio...
71 篇 humans
70 篇 shape
68 篇 robustness
66 篇 computer science
63 篇 image reconstruc...
54 篇 image classifica...
54 篇 learning (artifi...
49 篇 application soft...
49 篇 image motion ana...
41 篇 image representa...
40 篇 testing

机构

8 篇 microsoft resear...
6 篇 microsoft res as...
4 篇 robotics institu...
4 篇 carnegie mellon ...
4 篇 department of co...
4 篇 univ illinois ur...
4 篇 microsoft res re...
4 篇 department of co...
4 篇 mit cambridge ma...
4 篇 carnegie mellon ...
4 篇 cornell univ ith...
4 篇 department of co...
4 篇 stanford univ st...
4 篇 carnegie mellon ...
3 篇 penn state univ ...
3 篇 nanyang technol ...
3 篇 univ michigan an...
3 篇 univ adelaide sc...
3 篇 school of comput...
3 篇 georgia institut...

作者

6 篇 mubarak shah
6 篇 tsuhan chen
5 篇 shiguang shan
5 篇 daniel cremers
5 篇 xilin chen
5 篇 nikos paragios
5 篇 wen gao
5 篇 yanxi liu
4 篇 nassir navab
4 篇 zhang lei
4 篇 jan-michael frah...
4 篇 li stan z.
4 篇 thomas huang
4 篇 vincent lepetit
4 篇 tieniu tan
4 篇 svetha venkatesh
4 篇 narendra ahuja
4 篇 alan yuille
4 篇 de la torre fern...
4 篇 liang wang

语言

653 篇 英文
2 篇 土耳其文
1 篇 其他

检索条件"任意字段=26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013"

共 656 条记录，以下是181-190 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：

Exploring Compositional High Order pattern Potentials for Structured Output Learning

Exploring Compositional High Order Pattern Potentials for St...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Li, Yujia Tarlow, Daniel Zemel, Richard Univ Toronto Toronto ON M5S 3G4 Canada

ISBN: (纸本)9780769549897

When modeling structured outputs such as image segmentations, prediction can be improved by accurately modeling structure present in the labels. A key challenge is developing tractable models that are able to capture complex high level structure like shape. In this work, we study the learning of a general class of pattern-like high order potential, which we call Compositional High Order pattern Potentials (CHOPPs). We show that CHOPPs include the linear deviation pattern potentials of Rother et al. [] and also Restricted Boltzmann Machines (RBMs);we also establish the near equivalence of these two models. Experimentally, we show that performance is affected significantly by the degree of variability present in the datasets, and we define a quantitative variability measure to aid in studying this. We then improve CHOPPs performance in high variability datasets with two primary contributions: (a) developing a loss-sensitive joint learning procedure, so that internal pattern parameters can be learned in conjunction with other model potentials to minimize expected loss;and (b) learning an image-dependent mapping that encourages or inhibits patterns depending on image features. We also explore varying how multiple patterns are composed, and learning convolutional patterns. Quantitative results on challenging highly variable datasets show that the joint learning and image-dependent high order potentials can improve performance.

关键词： Boltzmann machines feature extraction image segmentation learning (artificial intelligence)

来源：评论

学校读者我要写书评

暂无评论

Supervised Kernel Descriptors for Visual recognition

Supervised Kernel Descriptors for Visual Recognition

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Wang, Peng Wang, Jingdong Zeng, Gang Xu, Weiwei Zha, Hongbin Li, Shipeng Peking Univ Beijing Peoples R China Microsoft Res Asia Beijing Peoples R China Hangzhou Normal Univ Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9780769549897

In visual recognition tasks, the design of low level image feature representation is fundamental. the advent of local patch features from pixel attributes such as SIFT and LBP, has precipitated dramatic progresses. Recently, a kernel view of these features, called kernel descriptors (KDES) [1], generalizes the feature design in an unsupervised fashion and yields impressive results. In this paper, we present a supervised framework to embed the image level label information into the design of patch level kernel descriptors, which we call supervised kernel descriptors (SKDES). Specifically, we adopt the broadly applied bag-of-words (BOW) image classification pipeline and a large margin criterion to learn the lowlevel patch representation, which makes the patch features much more compact and achieve better discriminative ability than KDES. With this method, we achieve competitive results over several public datasets comparing with state-of-the-art methods.

关键词： image classification image recognition image representation learning (artificial intelligence)

来源：评论

学校读者我要写书评

暂无评论

Fixation and Saccade based Face recognition from Single Image per Person with Various Occlusions and Expressions

Fixation and Saccade based Face Recognition from Single Imag...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Wei, Xingjie Li, Chang-Tsun Univ Warwick Dept Comp Sci Coventry CV4 7AL W Midlands England

ISBN: (纸本)9780769549903

Face recognition technique is widely used in the real-world applications over the past decade. Different from other biometric traits such as fingerprint and iris, face is the biological nature for humans to recognise a person even met just once. In this paper, we propose a novel method, which simulates the mechanism of fixations and saccades in human visual perception, to handle the face recognition from single image per person problem. Our method is robust to the local deformations of the face (i.e., expression changes and occlusions). Especially for the occlusion related problems, which have not received enough attentions compared with other challenging variations of illumination, expression and pose, our method significantly outperforms the state-of-the-art approaches despite various types of occlusions. Experimental results on the FRGC and the AR databases confirm the effectiveness of our method.

关键词： computer graphics face recognition

来源：评论

学校读者我要写书评

暂无评论

Kernel Null Space Methods for Novelty Detection

Kernel Null Space Methods for Novelty Detection

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Bodesheim, Paul Freytag, Alexander Rodner, Erik Kemmler, Michael Denzler, Joachim Univ Jena Comp Vis Grp D-07743 Jena Germany

ISBN: (纸本)9780769549897

Detecting samples from previously unknown classes is a crucial task in object recognition, especially when dealing with real-world applications where the closed-world assumption does not hold. We present how to apply a null space method for novelty detection, which maps all training samples of one class to a single point. Beside the possibility of modeling a single class, we are able to treat multiple known classes jointly and to detect novelties for a set of classes with a single model. In contrast to modeling the support of each known class individually, our approach makes use of a projection in a joint subspace where training samples of all known classes have zero intra-class variance. this subspace is called the null space of the training data. To decide about novelty of a test sample, our null space approach allows for solely relying on a distance measure instead of performing density estimation directly. therefore, we derive a simple yet powerful method for multi-class novelty detection, an important problem not studied sufficiently so far. Our novelty detection approach is assessed in comprehensive multi-class experiments using the publicly available datasets Caltech-256 and ImageNet. the analysis reveals that our null space approach is perfectly suited for multi-class novelty detection since it outperforms all other methods.

关键词： learning (artificial intelligence) object recognition

来源：评论

学校读者我要写书评

暂无评论

Weakly Supervised Learning of Mid-Level Features with Beta-Bernoulli Process Restricted Boltzmann Machines

Weakly Supervised Learning of Mid-Level Features with Beta-B...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Mittelman, Roni Lee, Honglak Kuipers, Benjamin Savarese, Silvio Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA

ISBN: (纸本)9780769549897

the use of semantic attributes in computer vision problems has been gaining increased popularity in recent years. Attributes provide an intermediate feature representation in between low-level features and the class categories, leading to improved learning on novel categories from few examples. However, a major caveat is that learning semantic attributes is a laborious task, requiring a significant amount of time and human intervention to provide labels. In order to address this issue, we propose a weakly supervised approach to learn mid-level features, where only class-level supervision is provided during training. We develop a novel extension of the restricted Boltzmann machine (RBM) by incorporating a Beta-Bernoulli process factor potential for hidden units. Unlike the standard RBM, our model uses the class labels to promote category-dependent sharing of learned features, which tends to improve the generalization performance. By using semantic attributes for which annotations are available, we show that we can find correspondences between the learned mid-level features and the labeled attributes. therefore, the mid-level features have distinct semantic characterization which is similar to that given by the semantic attributes, even though their labeling was not provided during training. Our experimental results on object recognition tasks show significant performance gains, outperforming existing methods which rely on manually labeled semantic attributes.

关键词： Boltzmann machines computer vision learning (artificial intelligence) object recognition

来源：评论

学校读者我要写书评

暂无评论

Anti-spoofing in action: joint operation with a verification system

Anti-spoofing in action: joint operation with a verification...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Chingovska, Ivana Anjos, Andre Marcel, Sebastien Idiap Res Inst CH-1920 Martigny Switzerland

ISBN: (纸本)9780769549903

Besides the recognition task, today's biometric systems need to cope with additional problem: spoofing attacks. Up to date, academic research considers spoofing as a binary classification problem: systems are trained to discriminate between real accesses and attacks. However, spoofing counter-measures are not designated to operate stand-alone, but as a part of a recognition system they will protect. In this paper, we study techniques for decision-level and score-level fusion to integrate a recognition and anti-spoofing systems, using an open-source framework that handles the ternary classification problem (clients, impostors and attacks) transparently. By doing so, we are able to report the impact of different spoofing counter-measures, fusion techniques and thresholding on the overall performance of the final recognition system. For a specific use-case covering face verification, experiments show to what extent simple fusion improves the trustworthiness of the system when exposed to spoofing attacks.

关键词： biometrics (access control) face recognition image classification security of data sensor fusion

来源：评论

学校读者我要写书评

暂无评论

Non-Rigid Structure from Motion with Diffusion Maps Prior

Non-Rigid Structure from Motion with Diffusion Maps Prior

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Tao, Lili Matuszewski, Bogdan J. Univ Cent Lancashire Appl Digital Signal & Image Proc Res Ctr Preston PR1 2HE Lancs England

ISBN: (纸本)9780769549897

In this paper, a novel approach based on a non-linear manifold learning technique is proposed to recover 3D non-rigid structures from 2D image sequences captured by a single camera. Most of the existing approaches assume that 3D shapes can be accurately modelled in a linear subspace. these techniques perform well when the deformations are relatively small or simple, but fail when more complex deformations need to be recovered. the non-linear deformations are often observed in highly flexible objects for which the use of the linear model is impractical. A specific type of shape variations might be governed by only a small number of parameters, therefore can be well-represented in a low dimensional manifold. We learn a nonlinear shape prior using diffusion maps method. the key contribution in this paper is the introduction of the shape prior that constrain the reconstructed shapes to lie in the learned manifold. the proposed methodology has been validated quantitatively and qualitatively on 2D points sequences projected from the 3D motion capture data and real 2D video sequences. the comparisons of the proposed manifold based method against several state-of-the-art techniques are shown on different types of deformable objects.

关键词： computer graphics image sequences shape recognition video signal processing

来源：评论

学校读者我要写书评

暂无评论

Collective Activity Detection using Hinge-loss Markov Random Fields

Collective Activity Detection using Hinge-loss Markov Random...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： London, Ben Khamis, Sameh Bach, Stephen H. Huang, Bert Getoor, Lise Davis, Larry Univ Maryland College Pk MD 20742 USA

ISBN: (纸本)9780769549903

We propose hinge-loss Markov random fields (HL-MRFs), a powerful class of continuous-valued graphical models, for high-level computer vision tasks. HL-MRFs are characterized by log-concave density functions, and are able to perform efficient, exact inference. their templated hinge-loss potential functions naturally encode soft-valued logical rules. Using the declarative modeling language probabilistic soft logic, one can easily define HL-MRFs via familiar constructs from first-order logic. We apply HL-MRFs to the task of activity detection, using principles of collective classification. Our model is simple, intuitive and interpretable. We evaluate our model on two datasets and show that it achieves significant lift over the low-level detectors.

关键词： Markov processes computer vision image classification object detection probabilistic logic random processes

来源：评论

学校读者我要写书评

暂无评论

Gauging Association patterns of Chromosome Territories via Chromatic Median

Gauging Association Patterns of Chromosome Territories via C...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Ding, Hu Stojkovic, Branislav Berezney, Ronald Xu, Jinhui SUNY Buffalo Dept Comp Sci & Engn Buffalo NY 14260 USA SUNY Buffalo Dept Biol Sci Buffalo NY 14260 USA

ISBN: (纸本)9780769549897

Computing accurate and robust organizational patterns of chromosome territories inside the cell nucleus is critical for understanding several fundamental genomic processes, such as co-regulation of gene activation, gene silencing, X chromosome inactivation, and abnormal chromosome rearrangement in cancer cells. the usage of advanced fluorescence labeling and image processing techniques has enabled researchers to investigate interactions of chromosome territories at large spatial resolution. the resulting high volume of generated data demands for high-throughput and automated image analysis methods. In this paper, we introduce a novel algorithmic tool for investigating association patterns of chromosome territories in a population of cells. Our method takes as input a set of graphs, one for each cell, containing information about spatial interaction of chromosome territories, and yields a single graph that contains essential information for the whole population and stands as its structural representative. We formulate this combinatorial problem as a semi-definite programming and present novel techniques to efficiently solve it. We validate our approach on both artificial and real biological data;the experimental results suggest that our approach yields a near-optimal solution, and can handle large-size datasets, which are significant improvements over existing techniques.

关键词： cellular biophysics graph theory medical image processing organisational aspects pattern classification

来源：评论

学校读者我要写书评

暂无评论

Fusing Spatiotemporal Features and Joints for 3D Action recognition

Fusing Spatiotemporal Features and Joints for 3D Action Reco...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Zhu, Yu Chen, Wenbin Guo, Guodong W Virginia Univ Dept CSEE Morgantown WV 26506 USA

ISBN: (纸本)9780769549903

We present a novel approach to 3D human action recognition based on a feature-level fusion of spatiotemporal features and skeleton joints. First, 3D interest points detection and local feature description are performed to extract spatiotemporal motion information. then the frame difference and pairwise distances of skeleton joint positions are computed to characterize the spatial information of the joints in 3D space. these two features are complementary to each other. A fusion scheme is then proposed to combine them effectively based on the random forests method. the proposed approach is validated on three challenging 3D action datasets for human action recognition. Experimental results show that the proposed approach outperforms the state-of-the-art methods on all three datasets.

关键词： feature extraction gesture recognition image fusion image motion analysis image thinning stereo image processing trees (mathematics)

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66页 << < 15 16 17 18 19 20 21 22 23 24 > >>

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：